From a67bf592789d62944358915e3ce6af7eefc50c3a Mon Sep 17 00:00:00 2001 From: "J. Aravind" Date: Tue, 16 Jun 2020 09:29:40 +0200 Subject: [PATCH] Pre CRAN 0.1.4 p3 --- NEWS.md | 1 + R/FourPHFfit.bulk.R | 2 + R/gcdata.R | 2 + R/germination.indices.R | 2 + R/plot.FourPHFfit.R | 2 + README.html | 24 +- README.md | 12 +- docs/articles/Introduction.html | 1467 +++++++++++------ .../figure-html/unnamed-chunk-9-1.png | Bin 8515 -> 13776 bytes docs/index.html | 10 +- docs/news/index.html | 2 + docs/pkgdown.yml | 4 +- docs/reference/FourPHFfit.bulk.html | 4 +- docs/reference/FourPHFfit.html | 6 +- docs/reference/gcdata-1.png | Bin 51105 -> 140173 bytes docs/reference/gcdata-2.png | Bin 51636 -> 136414 bytes docs/reference/gcdata.html | 4 +- docs/reference/germination.indices.html | 4 +- docs/reference/plot.FourPHFfit-1.png | Bin 29577 -> 74006 bytes docs/reference/plot.FourPHFfit-2.png | Bin 29592 -> 74519 bytes docs/reference/plot.FourPHFfit-3.png | Bin 17741 -> 59962 bytes docs/reference/plot.FourPHFfit-4.png | Bin 17741 -> 59958 bytes docs/reference/plot.FourPHFfit-5.png | Bin 17113 -> 39768 bytes docs/reference/plot.FourPHFfit-6.png | Bin 17113 -> 39775 bytes docs/reference/plot.FourPHFfit-7.png | Bin 30025 -> 78238 bytes docs/reference/plot.FourPHFfit-8.png | Bin 30050 -> 78187 bytes docs/reference/plot.FourPHFfit.html | 4 +- docs/sitemap.xml | 22 +- man/FourPHFfit.bulk.Rd | 2 + man/gcdata.Rd | 2 + man/germination.indices.Rd | 2 + man/plot.FourPHFfit.Rd | 2 + vignettes/Introduction.pdf | Bin 620430 -> 715565 bytes 33 files changed, 1041 insertions(+), 539 deletions(-) diff --git a/NEWS.md b/NEWS.md index d812d66..e544c86 100644 --- a/NEWS.md +++ b/NEWS.md @@ -22,6 +22,7 @@ Goldberg (1971), Bilbro and Wanjura (1982), and Fakorede and Ayoola (1980). * Fixed documentation errors in `FourPHFfit` and `CVGermTime`. * Updated documentation for `GermSpeed`, `GermSpeedAccumulated`, `CUGerm` `MeanGermRate`, `SEGermRate`, `CVG`, `MeanGermTime`, `VarGermTime`, `SEGermTime`, `GermUncertainty`, `GermSynchrony`, `MeanGermPercent`, `MeanGermNumber`, `WeightGermPercent`, `TimsonsIndex`, `GermRateGeorge` and `GermSynchrony`. * Converted all equations in Rd files to `MathJax`using `mathjaxr` +* Added long running examples to `\donttest` in `germination.indices`, `plot.FourPHFfit`, `gcdata` and `FourPHFfit.bulk`. # germinationmetrics 0.1.3 diff --git a/R/FourPHFfit.bulk.R b/R/FourPHFfit.bulk.R index 2da6cf1..c473790 100644 --- a/R/FourPHFfit.bulk.R +++ b/R/FourPHFfit.bulk.R @@ -48,6 +48,7 @@ #' #' @examples #' +#' \donttest{ #' data(gcdata) #' #' counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05", @@ -59,6 +60,7 @@ #' intervals = 1:14, partial = TRUE, #' fix.y0 = TRUE, fix.a = TRUE, xp = c(10, 60), #' tmax = 20, tries = 3, umax = 90, umin = 10) +#' } #' FourPHFfit.bulk <- function(data, total.seeds.col, counts.intervals.cols, intervals, partial = TRUE, diff --git a/R/gcdata.R b/R/gcdata.R index 4de7e4b..a069593 100644 --- a/R/gcdata.R +++ b/R/gcdata.R @@ -41,6 +41,7 @@ #' #' @examples #' +#' \donttest{ #' data(gcdata) #' library(ggplot2) #' library(reshape2) @@ -91,5 +92,6 @@ #' germination.indices(gcdata, total.seeds.col = "Total Seeds", #' counts.intervals.cols = counts.per.intervals, #' intervals = 1:14, partial = TRUE, max.int = 5) +#' } #' "gcdata" diff --git a/R/germination.indices.R b/R/germination.indices.R index 4cef3de..4cb754d 100644 --- a/R/germination.indices.R +++ b/R/germination.indices.R @@ -182,6 +182,7 @@ #' #' @examples #' +#' \donttest{ #' data(gcdata) #' #' counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05", @@ -190,6 +191,7 @@ #' germination.indices(gcdata, total.seeds.col = "Total Seeds", #' counts.intervals.cols = counts.per.intervals, #' intervals = 1:14, partial = TRUE, max.int = 5) +#' } #' #' @seealso This function is a wrapper around the different functions for #' computation of single-value germination indices in diff --git a/R/plot.FourPHFfit.R b/R/plot.FourPHFfit.R index 9f1b2cd..6f3e1d5 100644 --- a/R/plot.FourPHFfit.R +++ b/R/plot.FourPHFfit.R @@ -61,6 +61,7 @@ #' #' @examples #' +#' \donttest{ #' x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0) #' y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40) #' int <- 1:length(x) @@ -93,6 +94,7 @@ #' # Without y axis limits adjustment #' plot(fit1, limits = FALSE) #' plot(fit2, limits = FALSE) +#' } #' plot.FourPHFfit <- function(x, rog = TRUE, t50.total = TRUE, t50.germ = TRUE, tmgr = TRUE, mgt = TRUE, uniformity = TRUE, diff --git a/README.html b/README.html index 250c4b2..efd6538 100644 --- a/README.html +++ b/README.html @@ -608,26 +608,26 @@
minimal R version License: GPL v3 CRAN_Status_Badge rstudio mirror downloads

-

develVersion

+

develVersion

-

Project Status: Active lifecycle Last-changedate Rdoc Zenodo DOI Analytics

+

Project Status: Active lifecycle Last-changedate Rdoc Zenodo DOI Analytics

Description

Provides functions to compute various germination indices such as germinability, median germination time, mean germination time, mean germination rate, speed of germination, Timson’s index, germination value, coefficient of uniformity of germination, uncertainty of germination process, synchrony of germination etc. from germination count data. Includes functions for fitting cumulative seed germination curves using four-parameter hill function and computation of associated parameters. See the vignette for more, including full list of citations for the methods implemented.

Installation

The package can be installed from CRAN as follows:

- +
if (!require('devtools')) install.packages('devtools')
+install.packages('germinationmetrics', dependencies=TRUE)

The development version can be installed from github as follows:

- +
devtools::install_github("aravind-j/germinationmetrics")

Detailed tutorial

For a detailed tutorial (vignette) on how to used this package type:

- +
browseVignettes(package = 'germinationmetrics')

The vignette for the latest version is also available online.

What’s new

To know whats new in this version type:

- +
news(package='germinationmetrics')

CRAN page

Github page

@@ -635,12 +635,12 @@

Zenodo DOI

Citing germinationmetrics

To cite the methods in the package use:

- +
citation("germinationmetrics")

 To cite the R package 'germinationmetrics' in publications use:
 
-  Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S. R., and Kalyani Srinivasan (2020).  germinationmetrics:
-  Seed Germination Indices and Curve Fitting. R package version 0.1.4,
+  Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S. R., and Kalyani Srinivasan (2020).  germinationmetrics: Seed
+  Germination Indices and Curve Fitting. R package version 0.1.4,
   https://github.com/aravind-j/germinationmetricshttps://cran.r-project.org/package=germinationmetrics.
 
 A BibTeX entry for LaTeX users is
@@ -654,8 +654,8 @@ 
Citing germinationmetrics

     note = {https://cran.r-project.org/package=germinationmetrics},
   }
 
-This free and open-source software implements academic research by the authors and co-workers. If you use it, please
-support the project by citing the package.
+This free and open-source software implements academic research by the authors and co-workers. If you use it, please support
+the project by citing the package.
diff --git a/README.md b/README.md index 0f2b190..661b21e 100644 --- a/README.md +++ b/README.md @@ -17,12 +17,12 @@ v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org [![rstudio mirror downloads](https://cranlogs.r-pkg.org/badges/grand-total/germinationmetrics?color=green)](https://CRAN.R-project.org/package=germinationmetrics) -[![develVersion](https://img.shields.io/badge/devel%20version-0.1.3.9000-orange.svg)](https://github.com/aravind-j/germinationmetrics) +[![develVersion](https://img.shields.io/badge/devel%20version-0.1.4-orange.svg)](https://github.com/aravind-j/germinationmetrics) [![Project Status: Active](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active) [![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://www.tidyverse.org/lifecycle/#stable) -[![Last-changedate](https://img.shields.io/badge/last%20change-2020--06--15-yellowgreen.svg)](https://github.com/aravind-j/germinationmetrics/commits/master) +[![Last-changedate](https://img.shields.io/badge/last%20change-2020--06--16-yellowgreen.svg)](https://github.com/aravind-j/germinationmetrics/commits/master) [![Rdoc](http://www.rdocumentation.org/badges/version/germinationmetrics)](http://www.rdocumentation.org/packages/germinationmetrics) [![Zenodo DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1219630.svg)](https://doi.org/10.5281/zenodo.1219630) @@ -98,8 +98,8 @@ citation("germinationmetrics") To cite the R package 'germinationmetrics' in publications use: - Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S. R., and Kalyani Srinivasan (2020). germinationmetrics: - Seed Germination Indices and Curve Fitting. R package version 0.1.4, + Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S. R., and Kalyani Srinivasan (2020). germinationmetrics: Seed + Germination Indices and Curve Fitting. R package version 0.1.4, https://github.com/aravind-j/germinationmetricshttps://cran.r-project.org/package=germinationmetrics. A BibTeX entry for LaTeX users is @@ -113,6 +113,6 @@ A BibTeX entry for LaTeX users is note = {https://cran.r-project.org/package=germinationmetrics}, } -This free and open-source software implements academic research by the authors and co-workers. If you use it, please -support the project by citing the package. +This free and open-source software implements academic research by the authors and co-workers. If you use it, please support +the project by citing the package. ``` diff --git a/docs/articles/Introduction.html b/docs/articles/Introduction.html index f2d8718..0e87ab0 100644 --- a/docs/articles/Introduction.html +++ b/docs/articles/Introduction.html @@ -105,7 +105,7 @@

The germinationmetrics Package: A Brief Introduction

Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S. R., and Kalyani Srinivasan

-

2020-06-15

+

2020-06-16

Source: vignettes/Introduction.Rmd @@ -295,8 +295,459 @@

Table 3 : Single-value germination indices implemented in germinationmetrics.

-
[1] "Package 'pander' and pandoc are required to generate this table"
- + ++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Germination indexFunctionDetailsUnitMeasuresReference
Germination percentage or Final germination percentage or Germinability (\(GP\))GermPercentIt is computed as follows.
\[GP = \frac{N_{g}}{N_{t}} \times 100\]
+Where, \(N_{g}\) is the number of germinated seeds and \(N_{t}\) is the total number of seeds.		Percentage (%)Germination capacityISTA (2015)
Time for the first germination or Germination time lag (\(t_{0}\))FirstGermTimeIt is the time for first germination to occur (e.g. First day of germination)timeGermination time +Edwards (1932); Czabator (1962); Goloff and Bazzaz (1975); Labouriau (1983a); Ranal (1999); Quintanilla et al. (2000) +
Time for the last germination (\(t_{g}\))LastGermTimeIt is the time for last germination to occur (e.g. Last day of germination)timeGermination timeEdwards (1932)
Time spread of germination or Germination distributionTimeSpreadGermIt is the difference between time for last germination (\(t_{g}\)) and time for first germination (\(t_{0}\)).
\[Time\,spread\,of\, germination = t_{g}-t_{0}\] +		timeGermination time +Al-Mudaris (1998); Schrader and Graves (2000); Kader (2005) +
Peak period of germination or Modal time of germinationPeakGermTimeIt is the time in which highest frequency of germinated seeds are observed and need not be unique.timeGermination timeRanal and Santana (2006)
Median germination time (\(t_{50}\)) (Coolbear)t50It is the time to reach 50% of final/maximum germination.
+With argument method specified as "coolbear", it is computed as follows.
\[t_{50}=T_{i}+\frac{(\frac{N+1}{2}-N_{i})(T_{j}-T_{i})}{N_{j}-N_{i}}\]
+Where, \(t_{50}\) is the median germination time, \(N\) is the final number of germinated seeds, and \(N_{i}\) and \(N_{j}\) are the total number of seeds germinated in adjacent counts at time \(T_{i}\) and \(T_{j}\) respectively, when \(N_{i} < \frac{N + 1}{2} < N_{j}\).		timeGermination timeCoolbear et al. (1984)
Median germination time (\(t_{50}\)) (Farooq)t50With argument method specified as "farooq", it is computed as follows.
\[t_{50}=T_{i}+\frac{(\frac{N}{2}-N_{i})(T_{j}-T_{i})}{N_{j}-N_{i}}\]
+Where, \(t_{50}\) is the median germination time, \(N\) is the final number of germinated seeds, and \(N_{i}\) and \(N_{j}\) are the total number of seeds germinated in adjacent counts at time \(T_{i}\) and \(T_{j}\) respectively, when \(N_{i} < \frac{N}{2} < N_{j}\).		timeGermination timeFarooq et al. (2005)
Mean germination time or Mean length of incubation time (\(\overline{T}\)) or Germination resistance (\(GR\)) or Sprouting index (\(SI\)) or Emergence index (\(EI\))MeanGermTimeIt is the average length of time required for maximum germination of a seed lot and is estimated according to the following formula.
\[\overline{T} = +\frac{\sum_{i=1}^{k}N_{i}T_{i}}{\sum_{i=1}^{k}N_{i}}\]
+Where, \(T_{i}\) is the time from the start of the experiment to the \(i\)th interval, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(k\) is the total number of time intervals.
+It is the inverse of mean germination rate (\(\overline{V}\)).
\[\overline{T} = \frac{1}{\overline{V}}\] +		timeGermination time +Edmond and Drapala (1958); Czabator (1962); Smith and Millet (1964); Gordon (1969); Gordon (1971); Mock and Eberhart (1972); Ellis and Roberts (1980) Labouriau (1983a); Ranal and Santana (2006) +
Variance of germination time (\(s_{T}^{2}\))VarGermTimeIt is computed according to the following formula.
\[s_{T}^{2} = +\frac{\sum_{i=1}^{k}N_{i}(T_{i}-\overline{T})^{2}}{\sum_{i=1}^{k}N_{i}-1}\]
+Where, \(T_{i}\) is the time from the start of the experiment to the \(i\)th interval, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(k\) is the total number of time intervals.		timeGermination time +Labouriau (1983a); Ranal and Santana (2006) +
Standard error of germination time (\(s_{\overline{T}}\))SEGermTimeIt signifies the accuracy of the calculation of the mean germination time.
+It is estimated according to the following formula:
\[s_{\overline{T}} = +\sqrt{\frac{s_{T}^{2}}{\sum_{i=1}^{k}N_{i}}}\]
+Where, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval) and \(k\) is the total number of time intervals.		timeGermination time +Labouriau (1983a); Ranal and Santana (2006) +
Mean germination rate (\(\overline{V}\))MeanGermRateIt is computed according to the following formula:
\[\overline{V} = +\frac{\sum_{i=1}^{k}N_{i}}{\sum_{i=1}^{k}N_{i}T_{i}}\]
+Where, \(T_{i}\) is the time from the start of the experiment to the \(i\)th interval, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(k\) is the total number of time intervals.
+It is the inverse of mean germination time (\(\overline{T}\)).
\[\overline{V} = \frac{1}{\overline{T}}\] +		time-1 +Germination rate +Labouriau and Valadares (1976); Labouriau (1983b); Ranal and Santana (2006) +
Coefficient of velocity of germination (\(CVG\)) or Coefficient of rate of germination (\(CRG\)) or Kotowski’s coefficient of velocityCVGIt is estimated according to the following formula.
\[CVG = +\frac{\sum_{i=1}^{k}N_{i}}{\sum_{i=1}^{k}N_{i}T_{i}} +\times 100\]
\[CVG = \overline{V} \times 100\]
+Where, \(T_{i}\) is the time from the start of the experiment to the \(i\)th interval, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(k\) is the total number of time intervals.		% day -1 +Germination rate +Kotowski (1926), Nichols and Heydecker (1968); Bewley and Black (1994); Labouriau (1983b); Scott et al. (1984) +
Variance of germination rate (\(s_{V}^{2}\))VarGermRateIt is calculated according to the following formula.
\[s_{V}^{2} = \overline{V}^{4} \times s_{T}^{2}\]
+Where, \(s_{T}^{2}\) is the variance of germination time.		time-2 +Germination rate +Labouriau (1983b); Ranal and Santana (2006) +
Standard error of germination rate (\(s_{\overline{V}}\))SEGermRateIt is estimated according to the following formula.
\[s_{\overline{V}} = +\sqrt{\frac{s_{V}^{2}}{\sum_{i=1}^{k}N_{i}}}\]
+Where, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(k\) is the total number of time intervals.		time-1 +Germination rate +Labouriau (1983b); Ranal and Santana (2006) +
Germination rate as the reciprocal of the median time (\(v_{50}\))GermRateRecipIt is the reciprocal of the median germination time (\(t_{50}\)).
\[v_{50} = \frac{1}{t_{50}}\] +		time-1 +Germination rate +Went (1957); Labouriau (1983b); Ranal and Santana (2006) +
Speed of germination or Germination rate Index or index of velocity of germination or Emergence rate index (Allan, Vogel and Peterson; Erbach; Hsu and Nelson) or Germination index (AOSA)GermSpeedIt is the rate of germination in terms of the total number of seeds that germinate in a time interval.
+It is estimated as follows.
\[S = \sum_{i=1}^{k}\frac{N_{i}}{T_{i}}\]
+Where, \(T_{i}\) is the time from the start of the experiment to the
\(i\)th interval, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(k\) is the total number of time intervals.
+Instead of germination counts, germination percentages may also be used for computation of speed of germination.		% time-1 +Mixed +Throneberry and Smith (1955); Maguire (1962); Allan et al. (1962); Kendrick and Frankland (1969); Bouton et al. (1976); Erbach (1982); AOSA (1983); Khandakar and Bradbeer (1983); Hsu and Nelson (1986); Bradbeer (1988); Wardle et al. (1991) +
Speed of accumulated germinationGermSpeedAccumulatedIt is the rate of germination in terms of the accumulated/cumulative total number of seeds that germinate in a time interval.
+It is estimated as follows.
\[S_{accumulated} = +\sum_{i=1}^{k}\frac{\sum_{j=1}^{i}N_{j}}{T_{i}}\]
+Where, \(T_{i}\) is the time from the start of the experiment to the
\(i\)th interval, \(\sum_{j=1}^{i}N_{j}\) is the cumuative/accumulated number of seeds germinated in the \(i\)th interval, and \(k\) is the total number of time intervals.
+Instead of germination counts, germination percentages may also be used for computation of speed of germination.		% time-1 +Mixed +Bradbeer (1988); Wardle et al. (1991); Haugland and Brandsaeter (1996); Santana and Ranal (2004) +
Corrected germination rate indexGermSpeedCorrectedIt is computed as follows.
\[S_{corrected} = \frac{S}{FGP}\]
+Where, \(FGP\) is the final germination percentage or germinability.		time-1 +MixedEvetts and Burnside (1972)
Weighted germination percentage (\(WGP\))WeightGermPercentIt is estimated as follows.
\[WGP = \frac{\sum_{i=1}^{k}(k-i+1)N_{i}}{k \times +N} \times 100\]
+Where, \(N_{i}\) is the number of seeds that germinated in the time interval \(i\) (not cumulative, but partial count), \(N\) is the total number of seeds tested, and \(k\) is the total number of time intervals.		Mixed +Reddy et al. (1985); Reddy (1978) +
Mean germination percentage per unit time (\(\overline{GP}\))MeanGermPercentIt is estimated as follows.
\[\overline{GP} = \frac{GP}{T_{k}}\]
+Where, \(GP\) is the final germination percentage, \(T_{k}\) is the time at the \(k\)th time interval, and \(k\) is the total number of time intervals required for final germination.		MixedCzabator (1962)
Number of seeds germinated per unit time \(\overline{N}\) +MeanGermNumberIt is estimated as follows.
\[\overline{N} = \frac{N_{g}}{T_{k}}\]
+Where, \(N_{g}\) is the number of germinated seeds at the end of the germination test, \(T_{k}\) is the time at the \(k\)th time interval, and \(k\) is the total number of time intervals required for final germination.		MixedKhamassi et al. (2013)
Timson’s index [\(\sum 10\) (Ten summation), \(\sum 5\) or \(\sum 20\)] or Germination energy index (\(GEI\))TimsonsIndexIt is the progressive total of cumulative germination percentage recorded at specific intervals for a set period of time and is estimated in terms of cumulative germination percentage (\(G_{i}\)) as follows.
\[\Sigma k = \sum_{i=1}^{k}G_{i}\]
+Where, \(G_{i}\) is the cumulative germination percentage in time interval \(i\), and \(k\) is the total number of time intervals.
+It also estimated in terms of partial germination percentage as follows.
\[\Sigma k = \sum_{i=1}^{k}g_{i}(k-j)\]
+Where, \(g_{i}\) is the germination (not cumulative, but partial germination) in time interval \(i\) (\(i\) varying from \(0\) to \(k\)), \(k\) is the total number of time intervals, and \(j = i - 1\).		Mixed +Grose and Zimmer (1958); Timson (1965); Lyon and Coffelt (1966); Chaudhary and Ghildyal (1970); Negm and Smith (1978); Brown and Mayer (1988); Baskin and Baskin (1998); Goodchild and Walker (1971) +
Modified Timson’s index (\(\Sigma k_{mod}\)) (Labouriau)TimsonsIndexIt is estimated as Timson’s index \(\Sigma k\) divided by the sum of partial germination percentages.
\[\Sigma k_{mod} = \frac{\Sigma +k}{\sum_{i=1}^{k}g_{i}}\] +		MixedRanal and Santana (2006)
Modified Timson’s index (\(\Sigma k_{mod}\)) (Khan and Unger)TimsonsIndexIt is estimated as Timson’s index (\(\Sigma k\)) divided by the total time period of germination (\(T_{k}\)).
\[\Sigma k_{mod} = \frac{\Sigma k}{T_{k}}\] +		MixedKhan and Ungar (1984)
George’s index (\(GR\))GermRateGeorgeIt is estimated as follows.
\[GR = \sum_{i=1}^{k}N_{i}K_{i}\]
+Where \(N_{i}\) is the number of seeds germinated by \(i\)th interval and \(K_{i}\) is the number of intervals(eg. days) until the end of the test, and and \(k\) is the total number of time intervals.		Mixed +George (1961); Tucker and Wright (1965); Nichols and Heydecker (1968) +
Germination Index (\(GI\)) (Melville)GermIndexIt is estimated as follows.
\[GI = \sum_{i=1}^{k}\frac{\left | \left ( T_{k} - +T_{i} \right ) N_{i}\right |}{N_{t}}\]
+Where, \(T_{i}\) is the time from the start of the experiment to the \(i\)th interval (day for the example), \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), \(N_{t}\) is the total number of seeds used in the test, and \(k\) is the total number of time intervals.		MixedMelville et al. (1980)
Germination Index (\(GI_{mod}\)) (Melville; Santana and Ranal)GermIndexIt is estimated as follows.
\[GI_{mod} = \sum_{i=1}^{k}\frac{\left | \left ( +T_{k} - T_{i} \right ) N_{i}\right |}{N_{g}}\]
+Where, \(T_{i}\) is the time from the start of the experiment to the \(i\)th interval (day for the example), \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), \(N_{g}\) is the total number of germinated seeds at the end of the test, and \(k\) is the total number of time intervals.		Mixed +Melville et al. (1980); Santana and Ranal (2004); Ranal and Santana (2006) +
Emergence Rate Index (\(ERI\)) or Germination Rate Index (Shmueli and Goldberg)EmergenceRateIndexIt is estimated as follows.
\[ERI = \sum_{i=i_{0}}^{k-1}N_{i}(k-i)\]
+Where, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), \(i_{0}\) is the time interval when emergence/germination started, and \(k\) is the total number of time intervals.		MixedShmueli and Goldberg (1971)
Modified Emergence Rate Index (\(ERI_{mod}\)) or Modified Germination Rate Index (Shmueli and Goldberg; Santana and Ranal)EmergenceRateIndexIt is estimated by dividing Emergence rate index (\(ERI\)) by total number of emerged seedlings (or germinated seeds).
\[ERI_{mod} = +\frac{\sum_{i=i_{0}}^{k-1}N_{i}(k-i)}{N_{g}} = +\frac{ERI}{N_{g}}\]
+Where, \(N_{g}\) is the total number of germinated seeds at the end of the test, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), \(i_{0}\) is the time interval when emergence/germination started, and \(k\) is the total number of time intervals.		Mixed +Shmueli and Goldberg (1971); Santana and Ranal (2004); Ranal and Santana (2006) +
Emergence Rate Index (\(ERI\)) or Germination Rate Index (Bilbro & Wanjura)EmergenceRateIndexIt is the estimated as follows.
\[ERI = \frac{\sum_{i=1}^{k}N_{i}}{\overline{T}} = +\frac{N_{g}}{\overline{T}}\]
+Where, \(N_{g}\) is the total number of germinated seeds at the end of the test, \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(\overline{T}\) is the mean germination time or mean emergence time.		MixedBilbro and Wanjura (1982)
Emergence Rate Index (\(ERI\)) or Germination Rate Index (Fakorede)EmergenceRateIndexIt is estimated as follows.
\[ERI = \frac{\overline{T}}{FGP/100}\]
+Where, \(\overline{T}\) is the Mean germination time and \(FGP\) is the final germination time.		Mixed +Fakorede and Ayoola (1980); Fakorede and Ojo (1981); Fakorede and Agbana (1983) +
Peak value(\(PV\)) (Czabator) or Emergence Energy (\(EE\))PeakValueIt is the accumulated number of seeds germinated at the point on the germination curve at which the rate of germination starts to decrease. It is computed as the maximum quotient obtained by dividing successive cumulative germination values by the relevant incubation time.
\[PV = \max\left ( +\frac{G_{1}}{T_{1}},\frac{G_{2}}{T_{2}},\cdots +\frac{G_{k}}{T_{k}} \right )\]
+Where, \(T_{i}\) is the time from the start of the experiment to the
\(i\)th interval, \(G_{i}\) is the cumulative germination percentage in the \(i\)th time interval, and \(k\) is the total number of time intervals.		% time-1 +Mixed +Czabator (1962); Bonner (1967) +
Germination value (\(GV\)) (Czabator)GermValueIt is computed as follows.
\[GV = PV \times MDG\]
+Where, \(PV\) is the peak value and \(MDG\) is the mean daily germination percentage from the onset of germination.
+It can also be computed for other time intervals of successive germination counts, by replacing \(MDG\) with the mean germination percentage per unit time (\(\overline{GP}\)).
\(GV\) value can be modified (\(GV_{mod}\)), to consider the entire duration from the beginning of the test instead of just from the onset of germination.		Mixed +Czabator (1962); Brown and Mayer (1988) +
Germination value (\(GV\)) (Diavanshir and Pourbiek)GermValueIt is computed as follows.
\[GV = \frac{\sum DGS}{N} \times GP \times c\]
+Where, \(DGS\) is the daily germination speed computed by dividing cumulative germination percentage by the number of days since the since the onset of germination, \(N\) is the frequency or number of DGS calculated during the test, \(GP\) is the germination percentage expressed over 100, and \(c\) is a constant. The value of \(c\) is decided on the basis of average daily speed of germination (\(\frac{\sum DGS}{N}\)). If it is less than 10, then \(c\) value of 10 can be used and if it is more than 10, then value of 7 or 8 can be used for \(c\).
\(GV\) value can be modified (\(GV_{mod}\)), to consider the entire duration from the beginning of the test instead of just from the onset of germination.		Mixed +Djavanshir and Pourbeik (1976); Brown and Mayer (1988) +
Coefficient of uniformity of germination (\(CUG\))CUGermIt is computed as follows.
\[CUG = +\frac{\sum_{i=1}^{k}N_{i}}{\sum_{i=1}^{k}(\overline{T}-T_{i})^{2}N_{i}}\]
+Where, \(\overline{T}\) is the the mean germination time, \(T_{i}\) is the time from the start of the experiment to the \(i\)th interval (day for the example), \(N_{i}\) is the number of seeds germinated in the \(i\)th time interval (not the accumulated number, but the number corresponding to the \(i\)th interval), and \(k\) is the total number of time intervals.		Germination unifromity +Heydecker (1972); Bewley and Black (1994) +
Coefficient of variation of the germination time (\(CV_{T}\))CVGermTimeIt is estimated as follows.
\[CV_{T} = +\sqrt{\frac{s_{T}^{2}}{\overline{T}}}\]
+Where, \(s_{T}^{2}\) is the variance of germination time and \(\overline{T}\) is the mean germination time.		Germination unifromity +Gomes (1960); Ranal and Santana (2006) +
Synchronization index (\(\overline{E}\)) or Uncertainty of the germination process (\(U\)) or informational entropy (\(H\))GermUncertaintyIt is estimated as follows.
\[\overline{E} = +-\sum_{i=1}^{k}f_{i}\log_{2}f_{i}\]
+Where, \(f_{i}\) is the relative frequency of germination (\(f_{i}=\frac{N_{i}}{\sum_{i=1}^{k}N_{i}}\)), \(N_{i}\) is the number of seeds germinated on the \(i\)th time interval, and \(k\) is the total number of time intervals.		bitGermination synchrony +Shannon (1948); Labouriau and Valadares (1976); Labouriau (1983b) +
Synchrony of germination (\(Z\) index)GermSynchronyIt is computed as follows.
\[Z=\frac{\sum_{i=1}^{k}C_{N_{i},2}}{C_{\Sigma +N_{i},2}}\]
+Where, \(C_{N_{i},2}\) is the partial combination of the two germinated seeds from among \(N_{i}\), the number of seeds germinated on the \(i\)th time interval (estimated as \(C_{N_{i},2}=\frac{N_{i}(N_{i}-1)}{2}\)), and \(C_{\Sigma N_{i},2}\) is the partial combination of the two germinated seeds from among the total number of seeds germinated at the final count, assuming that all seeds that germinated did so simultaneously.		Germination synchrony +Primack (1985); Ranal and Santana (2006) +

@@ -306,16 +757,16 @@

GermPercent()

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 
 # From partial germination counts
 GermPercent(germ.counts = x, total.seeds = 50)

 
[1] 80

-
# From cumulative germination counts
+
# From cumulative germination counts
 GermPercent(germ.counts = y, total.seeds = 50, partial = FALSE)

 
[1] 80

-
# From number of germinated seeds
+
# From number of germinated seeds
 GermPercent(germinated.seeds = 40, total.seeds = 50)

 
[1] 80

 

@@ -323,7 +774,7 @@ 

 

 FirstGermTime(), LastGermTime(), PeakGermTime(), TimeSpreadGerm()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 z <- c(0, 0, 0, 0, 11, 11, 9, 7, 1, 0, 1, 0, 0, 0)
 int <- 1:length(x)
@@ -332,28 +783,28 @@ 

 #----------------------------------------------------------------------------
 FirstGermTime(germ.counts = x, intervals = int)

 
[1] 5

-
LastGermTime(germ.counts = x, intervals = int)

+
LastGermTime(germ.counts = x, intervals = int)

 
[1] 11

-
TimeSpreadGerm(germ.counts = x, intervals = int)

+
TimeSpreadGerm(germ.counts = x, intervals = int)

 
[1] 6

-
PeakGermTime(germ.counts = x, intervals = int)

+
PeakGermTime(germ.counts = x, intervals = int)

 
[1] 6

-
# For multiple peak germination times
+
# For multiple peak germination times
 PeakGermTime(germ.counts = z, intervals = int)

 
Warning in PeakGermTime(germ.counts = z, intervals = int): Multiple peak
 germination times exist.

 
[1] 5 6

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 FirstGermTime(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 5

-
LastGermTime(germ.counts = y, intervals = int, partial = FALSE)

+
LastGermTime(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 11

-
TimeSpreadGerm(germ.counts = y, intervals = int, partial = FALSE)

+
TimeSpreadGerm(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 6

-
PeakGermTime(germ.counts = y, intervals = int, partial = FALSE)

+
PeakGermTime(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 6

-
# For multiple peak germination time
+
# For multiple peak germination time
 PeakGermTime(germ.counts = cumsum(z), intervals = int, partial = FALSE)

 
Warning in PeakGermTime(germ.counts = cumsum(z), intervals = int, partial =
 FALSE): Multiple peak germination times exist.

@@ -363,7 +814,7 @@ 

 

 t50()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -371,20 +822,20 @@ 

 #----------------------------------------------------------------------------
 t50(germ.counts = x, intervals = int, method = "coolbear")

 
[1] 5.970588

-
t50(germ.counts = x, intervals = int, method = "farooq")

+
t50(germ.counts = x, intervals = int, method = "farooq")

 
[1] 5.941176

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 t50(germ.counts = y, intervals = int, partial = FALSE, method = "coolbear")

 
[1] 5.970588

-
t50(germ.counts = y, intervals = int, partial = FALSE, method = "farooq")

+
t50(germ.counts = y, intervals = int, partial = FALSE, method = "farooq")

 
[1] 5.941176

 

 

 

 MeanGermTime(), VarGermTime(), SEGermTime(), CVGermTime()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -392,28 +843,28 @@ 

 #----------------------------------------------------------------------------
 MeanGermTime(germ.counts = x, intervals = int)

 
[1] 6.7

-
VarGermTime(germ.counts = x, intervals = int)

+
VarGermTime(germ.counts = x, intervals = int)

 
[1] 1.446154

-
SEGermTime(germ.counts = x, intervals = int)

+
SEGermTime(germ.counts = x, intervals = int)

 
[1] 0.1901416

-
CVGermTime(germ.counts = x, intervals = int)

+
CVGermTime(germ.counts = x, intervals = int)

 
[1] 0.1794868

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 MeanGermTime(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 6.7

-
VarGermTime(germ.counts = y, intervals = int, partial = FALSE)

+
VarGermTime(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 19.04012

-
SEGermTime(germ.counts = y, intervals = int, partial = FALSE)

+
SEGermTime(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 0.2394781

-
CVGermTime(germ.counts = y, intervals = int, partial = FALSE)

+
CVGermTime(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 0.6512685

 

 

 

 MeanGermRate(), CVG(), VarGermRate(), SEGermRate(), GermRateRecip()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -421,30 +872,30 @@ 

 #----------------------------------------------------------------------------
 MeanGermRate(germ.counts = x, intervals = int)

 
[1] 0.1492537

-
CVG(germ.counts = x, intervals = int)

+
CVG(germ.counts = x, intervals = int)

 
[1] 14.92537

-
VarGermRate(germ.counts = x, intervals = int)

+
VarGermRate(germ.counts = x, intervals = int)

 
[1] 0.0007176543

-
SEGermRate(germ.counts = x, intervals = int)

+
SEGermRate(germ.counts = x, intervals = int)

 
[1] 0.004235724

-
GermRateRecip(germ.counts = x, intervals = int, method = "coolbear")

+
GermRateRecip(germ.counts = x, intervals = int, method = "coolbear")

 
[1] 0.1674877

-
GermRateRecip(germ.counts = x, intervals = int, method = "farooq")

+
GermRateRecip(germ.counts = x, intervals = int, method = "farooq")

 
[1] 0.1683168

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 MeanGermRate(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 0.1492537

-
CVG(germ.counts = y, intervals = int, partial = FALSE)

+
CVG(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 14.92537

-
VarGermRate(germ.counts = y, intervals = int, partial = FALSE)

+
VarGermRate(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 0.009448666

-
SEGermRate(germ.counts = y, intervals = int, partial = FALSE)

+
SEGermRate(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 0.005334776

-
GermRateRecip(germ.counts = y, intervals = int,
+
GermRateRecip(germ.counts = y, intervals = int,
               method = "coolbear", partial = FALSE)

 
[1] 0.1674877

-
GermRateRecip(germ.counts = y, intervals = int,
+
GermRateRecip(germ.counts = y, intervals = int,
               method = "farooq", partial = FALSE)

 
[1] 0.1683168

 

@@ -452,7 +903,7 @@ 

 

 GermSpeed(), GermSpeedAccumulated(), GermSpeedCorrected()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -460,40 +911,40 @@ 

 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = x, intervals = int)

 
[1] 6.138925

-
GermSpeedAccumulated(germ.counts = x, intervals = int)

+
GermSpeedAccumulated(germ.counts = x, intervals = int)

 
[1] 34.61567

-
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
+
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
                    method = "normal")

 
[1] 0.07673656

-
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
+
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
                    method = "accumulated")

 
[1] 0.4326958

-
# From partial germination counts (with percentages instead of counts)
+
# From partial germination counts (with percentages instead of counts)
 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = x, intervals = int,
           percent = TRUE, total.seeds = 50)

 
[1] 12.27785

-
GermSpeedAccumulated(germ.counts = x, intervals = int,
+
GermSpeedAccumulated(germ.counts = x, intervals = int,
                      percent = TRUE, total.seeds = 50)

 
[1] 69.23134

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 6.138925

-
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE)

+
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 34.61567

-
GermSpeedCorrected(germ.counts = y, intervals = int,
+
GermSpeedCorrected(germ.counts = y, intervals = int,
                    partial = FALSE, total.seeds = 50, method = "normal")

 
[1] 0.07673656

-
GermSpeedCorrected(germ.counts = y, intervals = int,
+
GermSpeedCorrected(germ.counts = y, intervals = int,
                    partial = FALSE, total.seeds = 50, method = "accumulated")

 
[1] 0.4326958

-
# From cumulative germination counts (with percentages instead of counts)
+
# From cumulative germination counts (with percentages instead of counts)
 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = y, intervals = int, partial = FALSE,
           percent = TRUE, total.seeds = 50)

 
[1] 12.27785

-
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE,
+
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE,
                      percent = TRUE, total.seeds = 50)

 
[1] 69.23134

 

@@ -501,7 +952,7 @@ 

 

 GermSpeed(), GermSpeedAccumulated(), GermSpeedCorrected()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -509,40 +960,40 @@ 

 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = x, intervals = int)

 
[1] 6.138925

-
GermSpeedAccumulated(germ.counts = x, intervals = int)

+
GermSpeedAccumulated(germ.counts = x, intervals = int)

 
[1] 34.61567

-
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
+
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
                    method = "normal")

 
[1] 0.07673656

-
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
+
GermSpeedCorrected(germ.counts = x, intervals = int, total.seeds = 50,
                    method = "accumulated")

 
[1] 0.4326958

-
# From partial germination counts (with percentages instead of counts)
+
# From partial germination counts (with percentages instead of counts)
 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = x, intervals = int,
           percent = TRUE, total.seeds = 50)

 
[1] 12.27785

-
GermSpeedAccumulated(germ.counts = x, intervals = int,
+
GermSpeedAccumulated(germ.counts = x, intervals = int,
                      percent = TRUE, total.seeds = 50)

 
[1] 69.23134

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 6.138925

-
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE)

+
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 34.61567

-
GermSpeedCorrected(germ.counts = y, intervals = int,
+
GermSpeedCorrected(germ.counts = y, intervals = int,
                    partial = FALSE, total.seeds = 50, method = "normal")

 
[1] 0.07673656

-
GermSpeedCorrected(germ.counts = y, intervals = int,
+
GermSpeedCorrected(germ.counts = y, intervals = int,
                    partial = FALSE, total.seeds = 50, method = "accumulated")

 
[1] 0.4326958

-
# From cumulative germination counts (with percentages instead of counts)
+
# From cumulative germination counts (with percentages instead of counts)
 #----------------------------------------------------------------------------
 GermSpeed(germ.counts = y, intervals = int, partial = FALSE,
           percent = TRUE, total.seeds = 50)

 
[1] 12.27785

-
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE,
+
GermSpeedAccumulated(germ.counts = y, intervals = int, partial = FALSE,
                      percent = TRUE, total.seeds = 50)

 
[1] 69.23134

 

@@ -550,7 +1001,7 @@ 

 

 WeightGermPercent()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -558,7 +1009,7 @@ 

 #----------------------------------------------------------------------------
 WeightGermPercent(germ.counts = x, total.seeds = 50, intervals = int)

 
[1] 47.42857

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 WeightGermPercent(germ.counts = y, total.seeds = 50, intervals = int,
                   partial = FALSE)

@@ -568,7 +1019,7 @@ 

 

 MeanGermPercent(), MeanGermNumber()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -576,15 +1027,15 @@ 

 #----------------------------------------------------------------------------
 MeanGermPercent(germ.counts = x, total.seeds = 50, intervals = int)

 
[1] 5.714286

-
MeanGermNumber(germ.counts = x, intervals = int)

+
MeanGermNumber(germ.counts = x, intervals = int)

 
[1] 2.857143

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 MeanGermPercent(germ.counts = y, total.seeds = 50, intervals = int, partial = FALSE)

 
[1] 5.714286

-
MeanGermNumber(germ.counts = y, intervals = int, partial = FALSE)

+
MeanGermNumber(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 2.857143

-
# From number of germinated seeds
+
# From number of germinated seeds
 #----------------------------------------------------------------------------
 MeanGermPercent(germinated.seeds = 40, total.seeds = 50, intervals = int)

 
[1] 5.714286

@@ -593,7 +1044,7 @@ 

 

 TimsonsIndex(), GermRateGeorge()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -602,73 +1053,73 @@ 

 # Wihout max specified
 TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50)

 
[1] 664

-
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
              modification = "none")

 
[1] 664

-
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
              modification = "labouriau")

 
[1] 8.3

-
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
              modification = "khanungar")

 
[1] 47.42857

-
GermRateGeorge(germ.counts = x, intervals = int)

+
GermRateGeorge(germ.counts = x, intervals = int)

 
[1] 332

-
# With max specified
+
# With max specified
 TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50, max = 10)

 
[1] 344

-
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
              max = 10, modification = "none")

 
[1] 344

-
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
              max = 10, modification = "labouriau")

 
[1] 4.410256

-
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
TimsonsIndex(germ.counts = x, intervals = int, total.seeds = 50,
              max = 10, modification = "khanungar")

 
[1] 24.57143

-
GermRateGeorge(germ.counts = x, intervals = int, max = 10)

+
GermRateGeorge(germ.counts = x, intervals = int, max = 10)

 
[1] 172

-
GermRateGeorge(germ.counts = x, intervals = int, max = 14)

+
GermRateGeorge(germ.counts = x, intervals = int, max = 14)

 
[1] 332

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 # Wihout max specified
 TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50)

 
[1] 664

-
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
+
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50,
              modification = "none")

 
[1] 664

-
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
+
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50,
              modification = "labouriau")

 
[1] 8.3

-
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
+
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50,
              modification = "khanungar")

 
[1] 47.42857

-
GermRateGeorge(germ.counts = y, intervals = int, partial = FALSE,)

+
GermRateGeorge(germ.counts = y, intervals = int, partial = FALSE,)

 
[1] 332

-
# With max specified
+
# With max specified
 TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50, max = 10)

 
[1] 344

-
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
+
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50,
              max = 10, modification = "none")

 
[1] 344

-
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
+
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50,
              max = 10, modification = "labouriau")

 
[1] 4.410256

-
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
+
TimsonsIndex(germ.counts = y, intervals = int, partial = FALSE,
              total.seeds = 50,
              max = 10, modification = "khanungar")

 
[1] 24.57143

-
GermRateGeorge(germ.counts = y, intervals = int, partial = FALSE,
+
GermRateGeorge(germ.counts = y, intervals = int, partial = FALSE,
                max = 10)

 
[1] 172

-
GermRateGeorge(germ.counts = y, intervals = int, partial = FALSE,
+
GermRateGeorge(germ.counts = y, intervals = int, partial = FALSE,
                max = 14)

 
[1] 332

 

@@ -676,7 +1127,7 @@ 

 

 GermIndex()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -684,22 +1135,22 @@ 

 #----------------------------------------------------------------------------
 GermIndex(germ.counts = x, intervals = int, total.seeds = 50)

 
[1] 5.84

-
GermIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
GermIndex(germ.counts = x, intervals = int, total.seeds = 50,
           modification = "none")

 
[1] 5.84

-
GermIndex(germ.counts = x, intervals = int, total.seeds = 50,
+
GermIndex(germ.counts = x, intervals = int, total.seeds = 50,
           modification = "santanaranal")

 
[1] 7.3

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 GermIndex(germ.counts = y, intervals = int, partial = FALSE,
           total.seeds = 50)

 
[1] 5.84

-
GermIndex(germ.counts = y, intervals = int, partial = FALSE,
+
GermIndex(germ.counts = y, intervals = int, partial = FALSE,
           total.seeds = 50,
           modification = "none")

 
[1] 5.84

-
GermIndex(germ.counts = y, intervals = int, partial = FALSE,
+
GermIndex(germ.counts = y, intervals = int, partial = FALSE,
           total.seeds = 50,
           modification = "santanaranal")

 
[1] 7.3

@@ -708,7 +1159,7 @@ 

 

 EmergenceRateIndex()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -716,32 +1167,32 @@ 

 #----------------------------------------------------------------------------
 EmergenceRateIndex(germ.counts = x, intervals = int)

 
[1] 292

-
EmergenceRateIndex(germ.counts = x, intervals = int,
+
EmergenceRateIndex(germ.counts = x, intervals = int,
                    method = "melville")

 
[1] 292

-
EmergenceRateIndex(germ.counts = x, intervals = int,
+
EmergenceRateIndex(germ.counts = x, intervals = int,
                    method = "melvillesantanaranal")

 
[1] 7.3

-
EmergenceRateIndex(germ.counts = x, intervals = int,
+
EmergenceRateIndex(germ.counts = x, intervals = int,
                    method = "bilbrowanjura")

 
[1] 5.970149

-
EmergenceRateIndex(germ.counts = x, intervals = int,
+
EmergenceRateIndex(germ.counts = x, intervals = int,
                    total.seeds = 50, method = "fakorede")

 
[1] 8.375

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,)

 
[1] 292

-
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
+
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
                    method = "melville")

 
[1] 292

-
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
+
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
                    method = "melvillesantanaranal")

 
[1] 7.3

-
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
+
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
                    method = "bilbrowanjura")

 
[1] 5.970149

-
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
+
EmergenceRateIndex(germ.counts = y, intervals = int, partial = FALSE,
                    total.seeds = 50, method = "fakorede")

 
[1] 8.375

 

@@ -749,7 +1200,7 @@ 

 

 PeakValue(), GermValue()
 

-
x <- c(0, 0, 34, 40, 21, 10, 4, 5, 3, 5, 8, 7, 7, 6, 6, 4, 0, 2, 0, 2)
+
x <- c(0, 0, 34, 40, 21, 10, 4, 5, 3, 5, 8, 7, 7, 6, 6, 4, 0, 2, 0, 2)
 y <- c(0, 0, 34, 74, 95, 105, 109, 114, 117, 122, 130, 137, 144, 150,
       156, 160, 160, 162, 162, 164)
 int <- 1:length(x)
@@ -759,7 +1210,7 @@ 

 #----------------------------------------------------------------------------
 PeakValue(germ.counts = x, intervals = int, total.seeds = 200)

 
[1] 9.5

-
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
           method = "czabator")

 
$`Germination Value`
 [1] 38.95
@@ -803,7 +1254,7 @@ 

 18 4.500000
 19 4.263158
 20 4.100000

-
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
           method = "dp", k = 10)

 
$`Germination Value`
 [1] 53.36595
@@ -850,7 +1301,7 @@ 

 
 $testend
 [1] 16

-
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
           method = "czabator", from.onset = FALSE)

 
$`Germination Value`
 [1] 38.95
@@ -898,7 +1349,7 @@ 

 18 4.500000
 19 4.263158
 20 4.100000

-
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = x, intervals = int, total.seeds = 200,
           method = "dp", k = 10, from.onset = FALSE)

 
$`Germination Value`
 [1] 46.6952
@@ -949,12 +1400,12 @@ 

 
 $testend
 [1] 16

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 PeakValue(germ.counts = y, interval = int, total.seeds = 200,
           partial = FALSE)

 
[1] 9.5

-
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
           partial = FALSE, method = "czabator")

 
$`Germination Value`
 [1] 38.95
@@ -998,7 +1449,7 @@ 

 18 4.500000
 19 4.263158
 20 4.100000

-
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
           partial = FALSE, method = "dp", k = 10)

 
$`Germination Value`
 [1] 53.36595
@@ -1045,7 +1496,7 @@ 

 
 $testend
 [1] 16

-
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
           partial = FALSE, method = "czabator", from.onset = FALSE)

 
$`Germination Value`
 [1] 38.95
@@ -1093,7 +1544,7 @@ 

 18 4.500000
 19 4.263158
 20 4.100000

-
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
+
GermValue(germ.counts = y, intervals = int, total.seeds = 200,
           partial = FALSE, method = "dp", k = 10, from.onset = FALSE)

 
$`Germination Value`
 [1] 46.6952
@@ -1149,7 +1600,7 @@ 

 

 CUGerm()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -1157,7 +1608,7 @@ 

 #----------------------------------------------------------------------------
 CUGerm(germ.counts = x, intervals = int)

 
[1] 0.7092199

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 CUGerm(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 0.05267935

@@ -1166,7 +1617,7 @@ 

 

 GermSynchrony(), GermUncertainty()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 
@@ -1174,13 +1625,13 @@ 

 #----------------------------------------------------------------------------
 GermSynchrony(germ.counts = x, intervals = int)

 
[1] 0.2666667

-
GermUncertainty(germ.counts = x, intervals = int)

+
GermUncertainty(germ.counts = x, intervals = int)

 
[1] 2.062987

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 GermSynchrony(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 0.2666667

-
GermUncertainty(germ.counts = y, intervals = int, partial = FALSE)

+
GermUncertainty(germ.counts = y, intervals = int, partial = FALSE)

 
[1] 2.062987

 

 

@@ -1198,7 +1649,117 @@ 

 
The details of various parameters that are computed from this function are given in Table 4.

 
Table 4 Germination parameters estimated from the four-parameter hill function.

 
-
[1] "Package 'pander' and pandoc are required to generate this table"

+
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Germination parametersDetailsUnitMeasures
y intercept (\(y_{0}\))The intercept on the y axis.
Asymptote (\(a\))It is the maximum cumulative germination percentage, which is equivalent to germination capacity.%Germination capacity
Shape and steepness (\(b\))Mathematical parameter controlling the shape and steepness of the germination curve. The larger the \(b\) , the steeper the rise toward the asymptote \(a\), and the shorter the time between germination onset and maximum germination.Germination rate
Half-maximal activation level (\(c\))Time required for 50% of viable seeds to germinate.timeGermination time
\(lag\)It is the time at germination onset and is computed by solving four-parameter hill function after setting y to 0 as follows.
\[lag = b\sqrt{\frac{-y_{0}c^{b}}{a + y_{0}}}\]
+		timeGermination time
\(D_{lag-50}\)The duration between the time at germination onset (\(lag\)) and that at 50% germination (\(c\)).timeGermination time
\(t_{50_{total}}\)Time required for 50% of total seeds to germinate.timeGermination time
\(t_{50_{germinated}}\)Time required for 50% of viable/germinated seeds to germinatetimeGermination time
\(t_{x_{total}}\)Time required for \(x\)% of total seeds to germinate.timeGermination time
\(t_{x_{germinated}}\)Time required for \(x\)% of viable/germinated seeds to germinatetimeGermination time
Uniformity (\(U_{t_{max}-t_{min}}\))It is the time interval between the percentages of viable seeds specified in the arguments umin and umin to germinate.timeGermination time
Time at maximum germination rate (\(TMGR\))The partial derivative of the four-parameter hill function gives the instantaneous rate of germination (\(s\)) as follows.
\[s = \frac{\partial y}{\partial x} =
+\frac{abc^{b}x^{b-1}}{(c^{b}+x^{b})^{2}}\]

+From this function for instantaneous rate of germination, \(TMGR\) can be estimated as follows.
\[TMGR = b \sqrt{\frac{c^{b}(b-1)}{b+1}}\]

+It represents the point in time when the instantaneous rate of germination starts to decline.		timeGermination time
Area under the curve (\(AUC\))It is obtained by integration of the fitted curve between time 0 and time specified in the argument tmax.Mixed
\(MGT\)Calculated by integration of the fitted curve and proper normalisation.timeGermination time
\(Skewness\)It is computed as follows.
\[\frac{MGT}{t_{50_{germinated}}}\]
+

 

 

 Examples

@@ -1207,7 +1768,7 @@ 

 

 FourPHFfit()
 

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
 y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
 int <- 1:length(x)
 total.seeds = 50
@@ -1234,9 +1795,9 @@ 

 
 $Parameters
   term  estimate  std.error statistic      p.value
-1    a 80.000000 1.24158595  64.43372 1.973240e-14
-2    b  9.881947 0.70779379  13.96162 6.952322e-08
-3    c  6.034954 0.04952654 121.85294 3.399385e-17
+1    a 80.000000 1.24158597  64.43372 1.973240e-14
+2    b  9.881947 0.70779381  13.96162 6.952324e-08
+3    c  6.034954 0.04952654 121.85294 3.399384e-17
 4   y0  0.000000 0.91607007   0.00000 1.000000e+00
 
 $Fit
@@ -1299,7 +1860,7 @@ 

 
 attr(,"class")
 [1] "FourPHFfit"

-
# From cumulative germination counts
+
# From cumulative germination counts
 #----------------------------------------------------------------------------
 FourPHFfit(germ.counts = y, intervals = int, total.seeds = 50, tmax = 20,
 partial = FALSE)

@@ -1387,43 +1948,40 @@ 

 
 attr(,"class")
 [1] "FourPHFfit"

-
x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
-y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
-int <- 1:length(x)
-total.seeds = 50
-
-# From partial germination counts
-#----------------------------------------------------------------------------
-fit1 <- FourPHFfit(germ.counts = x, intervals = int,
-                   total.seeds = 50, tmax = 20)
-
-# From cumulative germination counts
-#----------------------------------------------------------------------------
-fit2 <- FourPHFfit(germ.counts = y, intervals = int,
-                   total.seeds = 50, tmax = 20, partial = FALSE)
-
-# Default plots
-plot(fit1)

-

-
plot(fit2)

-

-
# No labels
-plot(fit1, plotlabels = FALSE)

-

-
plot(fit2, plotlabels = FALSE)

-

-
# Only the FPHF curve
-plot(fit1, rog = FALSE, t50.total = FALSE, t50.germ = FALSE,
-     tmgr = FALSE, mgt = FALSE, uniformity = FALSE)

-

-
plot(fit2, rog = FALSE, t50.total = FALSE, t50.germ = FALSE,
-     tmgr = FALSE, mgt = FALSE, uniformity = FALSE)

-

-
# Without y axis limits adjustment
-plot(fit1, limits = FALSE)

-

-
plot(fit2, limits = FALSE)

-

+
## No test: 
+##D x <- c(0, 0, 0, 0, 4, 17, 10, 7, 1, 0, 1, 0, 0, 0)
+##D y <- c(0, 0, 0, 0, 4, 21, 31, 38, 39, 39, 40, 40, 40, 40)
+##D int <- 1:length(x)
+##D total.seeds = 50
+##D 
+##D # From partial germination counts
+##D #----------------------------------------------------------------------------
+##D fit1 <- FourPHFfit(germ.counts = x, intervals = int,
+##D                    total.seeds = 50, tmax = 20)
+##D 
+##D # From cumulative germination counts
+##D #----------------------------------------------------------------------------
+##D fit2 <- FourPHFfit(germ.counts = y, intervals = int,
+##D                    total.seeds = 50, tmax = 20, partial = FALSE)
+##D 
+##D # Default plots
+##D plot(fit1)
+##D plot(fit2)
+##D 
+##D # No labels
+##D plot(fit1, plotlabels = FALSE)
+##D plot(fit2, plotlabels = FALSE)
+##D 
+##D # Only the FPHF curve
+##D plot(fit1, rog = FALSE, t50.total = FALSE, t50.germ = FALSE,
+##D      tmgr = FALSE, mgt = FALSE, uniformity = FALSE)
+##D plot(fit2, rog = FALSE, t50.total = FALSE, t50.germ = FALSE,
+##D      tmgr = FALSE, mgt = FALSE, uniformity = FALSE)
+##D 
+##D # Without y axis limits adjustment
+##D plot(fit1, limits = FALSE)
+##D plot(fit2, limits = FALSE)
+## End(No test)

 

 

 

@@ -1436,319 +1994,35 @@ 

 germination.indices()
 

 
This wrapper function can be used to compute several germination indices simultaneously for multiple samples in batch.

-
data(gcdata)
-
-counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05",
-                          "Day06", "Day07", "Day08", "Day09", "Day10",
-                          "Day11", "Day12", "Day13", "Day14")
-germination.indices(gcdata, total.seeds.col = "Total Seeds",
-                    counts.intervals.cols = counts.per.intervals,
-                    intervals = 1:14, partial = TRUE, max.int = 5)

-
   Genotype Rep Day01 Day02 Day03 Day04 Day05 Day06 Day07 Day08 Day09 Day10
-1        G1   1     0     0     0     0     4    17    10     7     1     0
-2        G2   1     0     0     0     1     3    15    13     6     2     1
-3        G3   1     0     0     0     2     3    18     9     8     2     1
-4        G4   1     0     0     0     0     4    19    12     6     2     1
-5        G5   1     0     0     0     0     5    20    12     8     1     0
-6        G1   2     0     0     0     0     3    21    11     7     1     1
-7        G2   2     0     0     0     0     4    18    11     7     1     0
-8        G3   2     0     0     0     1     3    14    12     6     2     1
-9        G4   2     0     0     0     1     3    19    10     8     1     1
-10       G5   2     0     0     0     0     4    18    13     6     2     1
-11       G1   3     0     0     0     0     5    21    11     8     1     0
-12       G2   3     0     0     0     0     3    20    10     7     1     1
-13       G3   3     0     0     0     0     4    19    12     8     1     1
-14       G4   3     0     0     0     0     3    21    11     6     1     0
-15       G5   3     0     0     0     0     4    17    10     8     1     1
-   Day11 Day12 Day13 Day14 Total Seeds GermPercent FirstGermTime LastGermTime
-1      1     0     0     0          50    80.00000             5           11
-2      0     1     0     0          51    82.35294             4           12
-3      1     1     0     0          48    93.75000             4           12
-4      1     1     0     0          51    90.19608             5           12
-5      0     1     1     0          50    96.00000             5           13
-6      1     1     0     0          49    93.87755             5           12
-7      1     0     0     0          48    87.50000             5           11
-8      0     1     0     0          47    85.10638             4           12
-9      1     1     0     0          52    86.53846             4           12
-10     0     1     0     0          50    90.00000             5           12
-11     0     1     1     0          51    94.11765             5           13
-12     1     1     0     0          51    86.27451             5           12
-13     0     1     1     0          49    95.91837             5           13
-14     1     1     0     0          48    91.66667             5           12
-15     1     0     0     0          48    87.50000             5           11
-   PeakGermTime TimeSpreadGerm t50_Coolbear t50_Farooq MeanGermTime VarGermTime
-1             6              6     5.970588   5.941176     6.700000    1.446154
-2             6              8     6.192308   6.153846     6.857143    2.027875
-3             6              8     6.000000   5.972222     6.866667    2.572727
-4             6              7     6.041667   6.000000     6.891304    2.187923
-5             6              8     5.975000   5.950000     6.812500    2.368351
-6             6              7     5.976190   5.952381     6.869565    2.071498
-7             6              6     5.972222   5.944444     6.690476    1.389663
-8             6              8     6.208333   6.166667     6.875000    2.112179
-9             6              8     6.000000   5.973684     6.866667    2.300000
-10            6              7     6.076923   6.038462     6.822222    1.831313
-11            6              8     5.928571   5.904762     6.791667    2.381206
-12            6              7     5.975000   5.950000     6.886364    2.149577
-13            6              8     6.083333   6.041667     6.936170    2.539315
-14            6              7     5.928571   5.904762     6.772727    1.900634
-15            6              6     6.050000   6.000000     6.809524    1.670151
-   SEGermTime CVGermTime MeanGermRate  VarGermRate  SEGermRate      CVG
-1   0.1901416  0.1794868    0.1492537 0.0007176543 0.004235724 14.92537
-2   0.2197333  0.2076717    0.1458333 0.0009172090 0.004673148 14.58333
-3   0.2391061  0.2335882    0.1456311 0.0011572039 0.005071059 14.56311
-4   0.2180907  0.2146419    0.1451104 0.0009701218 0.004592342 14.51104
-5   0.2221275  0.2259002    0.1467890 0.0010995627 0.004786184 14.67890
-6   0.2122088  0.2095140    0.1455696 0.0009301809 0.004496813 14.55696
-7   0.1818989  0.1761967    0.1494662 0.0006935558 0.004063648 14.94662
-8   0.2297923  0.2113940    0.1454545 0.0009454531 0.004861721 14.54545
-9   0.2260777  0.2208604    0.1456311 0.0010345321 0.004794747 14.56311
-10  0.2017321  0.1983606    0.1465798 0.0008453940 0.004334343 14.65798
-11  0.2227295  0.2272072    0.1472393 0.0011191581 0.004828643 14.72393
-12  0.2210295  0.2129053    0.1452145 0.0009558577 0.004660905 14.52145
-13  0.2324392  0.2297410    0.1441718 0.0010970785 0.004831366 14.41718
-14  0.2078370  0.2035568    0.1476510 0.0009033254 0.004531018 14.76510
-15  0.1994129  0.1897847    0.1468531 0.0007767634 0.004300508 14.68531
-   GermRateRecip_Coolbear GermRateRecip_Farooq GermSpeed_Count
-1               0.1674877            0.1683168        6.138925
-2               0.1614907            0.1625000        6.362698
-3               0.1666667            0.1674419        6.882179
-4               0.1655172            0.1666667        6.927417
-5               0.1673640            0.1680672        7.318987
-6               0.1673307            0.1680000        6.931782
-7               0.1674419            0.1682243        6.448449
-8               0.1610738            0.1621622        6.053175
-9               0.1666667            0.1674009        6.830592
-10              0.1645570            0.1656051        6.812698
-11              0.1686747            0.1693548        7.342796
-12              0.1673640            0.1680672        6.622258
-13              0.1643836            0.1655172        7.052320
-14              0.1686747            0.1693548        6.706782
-15              0.1652893            0.1666667        6.363925
-   GermSpeed_Percent GermSpeedAccumulated_Count GermSpeedAccumulated_Percent
-1           12.27785                   34.61567                     69.23134
-2           12.47588                   35.54058                     69.68741
-3           14.33787                   38.29725                     79.78594
-4           13.58317                   38.68453                     75.85202
-5           14.63797                   41.00786                     82.01571
-6           14.14649                   38.77620                     79.13509
-7           13.43427                   36.38546                     75.80304
-8           12.87909                   33.77079                     71.85275
-9           13.13575                   38.11511                     73.29829
-10          13.62540                   38.19527                     76.39054
-11          14.39764                   41.17452                     80.73436
-12          12.98482                   37.00640                     72.56158
-13          14.39249                   39.29399                     80.19182
-14          13.97246                   37.69490                     78.53103
-15          13.25818                   35.69697                     74.36868
-   GermSpeedCorrected_Normal GermSpeedCorrected_Accumulated WeightGermPercent
-1                 0.07673656                      0.4326958          47.42857
-2                 0.07726134                      0.4315642          47.89916
-3                 0.07340991                      0.4085040          54.46429
-4                 0.07680397                      0.4288937          52.24090
-5                 0.07623944                      0.4271652          56.14286
-6                 0.07383855                      0.4130508          54.51895
-7                 0.07369656                      0.4158338          51.93452
-8                 0.07112480                      0.3968068          49.39210
-9                 0.07893128                      0.4404413          50.27473
-10                0.07569665                      0.4243919          52.57143
-11                0.07801721                      0.4374793          55.18207
-12                0.07675799                      0.4289379          50.00000
-13                0.07352419                      0.4096608          55.24781
-14                0.07316490                      0.4112171          53.86905
-15                0.07273057                      0.4079653          51.19048
-   MeanGermPercent MeanGermNumber TimsonsIndex TimsonsIndex_Labouriau
-1         5.714286       2.857143     8.000000                   1.00
-2         5.882353       3.000000     9.803922                   1.25
-3         6.696429       3.214286    14.583333                   1.40
-4         6.442577       3.285714     7.843137                   1.00
-5         6.857143       3.428571    10.000000                   1.00
-6         6.705539       3.285714     6.122449                   1.00
-7         6.250000       3.000000     8.333333                   1.00
-8         6.079027       2.857143    10.638298                   1.25
-9         6.181319       3.214286     9.615385                   1.25
-10        6.428571       3.214286     8.000000                   1.00
-11        6.722689       3.428571     9.803922                   1.00
-12        6.162465       3.142857     5.882353                   1.00
-13        6.851312       3.357143     8.163265                   1.00
-14        6.547619       3.142857     6.250000                   1.00
-15        6.250000       3.000000     8.333333                   1.00
-   TimsonsIndex_KhanUngar GermRateGeorge GermIndex GermIndex_mod
-1               0.5714286              4  5.840000      7.300000
-2               0.7002801              5  5.882353      7.142857
-3               1.0416667              7  6.687500      7.133333
-4               0.5602241              4  6.411765      7.108696
-5               0.7142857              5  6.900000      7.187500
-6               0.4373178              3  6.693878      7.130435
-7               0.5952381              4  6.395833      7.309524
-8               0.7598784              5  6.063830      7.125000
-9               0.6868132              5  6.173077      7.133333
-10              0.5714286              4  6.460000      7.177778
-11              0.7002801              5  6.784314      7.208333
-12              0.4201681              3  6.137255      7.113636
-13              0.5830904              4  6.775510      7.063830
-14              0.4464286              3  6.625000      7.227273
-15              0.5952381              4  6.291667      7.190476
-   EmergenceRateIndex_Melville EmergenceRateIndex_Melville_mod
-1                          292                        7.300000
-2                          300                        7.142857
-3                          321                        7.133333
-4                          327                        7.108696
-5                          345                        7.187500
-6                          328                        7.130435
-7                          307                        7.309524
-8                          285                        7.125000
-9                          321                        7.133333
-10                         323                        7.177778
-11                         346                        7.208333
-12                         313                        7.113636
-13                         332                        7.063830
-14                         318                        7.227273
-15                         302                        7.190476
-   EmergenceRateIndex_BilbroWanjura EmergenceRateIndex_Fakorede PeakValue
-1                          5.970149                    8.375000  9.500000
-2                          6.125000                    8.326531  9.313725
-3                          6.553398                    7.324444 10.416667
-4                          6.675079                    7.640359 10.049020
-5                          7.045872                    7.096354 11.250000
-6                          6.696203                    7.317580 10.714286
-7                          6.277580                    7.646259 10.416667
-8                          5.818182                    8.078125  9.574468
-9                          6.553398                    7.934815  9.855769
-10                         6.596091                    7.580247 10.250000
-11                         7.067485                    7.216146 11.029412
-12                         6.389439                    7.981921  9.803922
-13                         6.776074                    7.231326 10.969388
-14                         6.496644                    7.388430 10.677083
-15                         6.167832                    7.782313 10.156250
-   GermValue_Czabator GermValue_DP GermValue_Czabator_mod GermValue_DP_mod
-1            54.28571     57.93890               54.28571         39.56076
-2            54.78662     52.58713               54.78662         40.99260
-3            69.75446     68.62289               69.75446         53.42809
-4            64.74158     70.43331               64.74158         48.86825
-5            77.14286     80.16914               77.14286         56.23935
-6            71.84506     76.51983               71.84506         53.06435
-7            65.10417     69.41325               65.10417         47.37690
-8            58.20345     56.00669               58.20345         43.67948
-9            60.92165     58.13477               60.92165         45.30801
-10           65.89286     70.91875               65.89286         49.10820
-11           74.14731     77.39782               74.14731         54.27520
-12           60.41632     64.44988               60.41632         44.71582
-13           75.15470     78.16335               75.15470         54.94192
-14           69.90947     74.40140               69.90947         51.41913
-15           63.47656     67.62031               63.47656         46.48043
-      CUGerm GermSynchrony GermUncertainty
-1  0.7092199     0.2666667        2.062987
-2  0.5051546     0.2346109        2.321514
-3  0.3975265     0.2242424        2.462012
-4  0.4672113     0.2502415        2.279215
-5  0.4312184     0.2606383        2.146051
-6  0.4934701     0.2792271        2.160545
-7  0.7371500     0.2729384        2.040796
-8  0.4855842     0.2256410        2.357249
-9  0.4446640     0.2494949        2.321080
-10 0.5584666     0.2555556        2.187983
-11 0.4288905     0.2686170        2.128670
-12 0.4760266     0.2737844        2.185245
-13 0.4023679     0.2506938        2.241181
-14 0.5383760     0.2991543        2.037680
-15 0.6133519     0.2497096        2.185028

+
## No test: 
+##D data(gcdata)
+##D 
+##D counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05",
+##D                           "Day06", "Day07", "Day08", "Day09", "Day10",
+##D                           "Day11", "Day12", "Day13", "Day14")
+##D germination.indices(gcdata, total.seeds.col = "Total Seeds",
+##D                     counts.intervals.cols = counts.per.intervals,
+##D                     intervals = 1:14, partial = TRUE, max.int = 5)
+## End(No test)

 

 

 

 FourPHFfit.bulk()
 

 
This wrapper function can be used to fit the four-parameter hill function for multiple samples in batch.

-
data(gcdata)
-
-counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05",
-                          "Day06", "Day07", "Day08", "Day09", "Day10",
-                          "Day11", "Day12", "Day13", "Day14")
-
-FourPHFfit.bulk(gcdata, total.seeds.col = "Total Seeds",
-                    counts.intervals.cols = counts.per.intervals,
-                    intervals = 1:14, partial = TRUE,
-                    fix.y0 = TRUE, fix.a = TRUE, xp = c(10, 60),
-                    tmax = 20, tries = 3, umax = 90, umin = 10)

-
    Genotype Rep Day01 Day02 Day03 Day04 Day05 Day06 Day07 Day08 Day09 Day10
- 1:       G1   1     0     0     0     0     4    17    10     7     1     0
- 2:       G2   1     0     0     0     1     3    15    13     6     2     1
- 3:       G3   1     0     0     0     2     3    18     9     8     2     1
- 4:       G4   1     0     0     0     0     4    19    12     6     2     1
- 5:       G5   1     0     0     0     0     5    20    12     8     1     0
- 6:       G1   2     0     0     0     0     3    21    11     7     1     1
- 7:       G2   2     0     0     0     0     4    18    11     7     1     0
- 8:       G3   2     0     0     0     1     3    14    12     6     2     1
- 9:       G4   2     0     0     0     1     3    19    10     8     1     1
-10:       G5   2     0     0     0     0     4    18    13     6     2     1
-11:       G1   3     0     0     0     0     5    21    11     8     1     0
-12:       G2   3     0     0     0     0     3    20    10     7     1     1
-13:       G3   3     0     0     0     0     4    19    12     8     1     1
-14:       G4   3     0     0     0     0     3    21    11     6     1     0
-15:       G5   3     0     0     0     0     4    17    10     8     1     1
-    Day11 Day12 Day13 Day14 Total Seeds        a         b        c y0 lag
- 1:     1     0     0     0          50 80.00000  9.881947 6.034954  0   0
- 2:     0     1     0     0          51 82.35294  9.227667 6.175193  0   0
- 3:     1     1     0     0          48 93.75000  7.793055 6.138110  0   0
- 4:     1     1     0     0          51 90.19608  8.925668 6.125172  0   0
- 5:     0     1     1     0          50 96.00000  9.419194 6.049641  0   0
- 6:     1     1     0     0          49 93.87755  9.450187 6.097412  0   0
- 7:     1     0     0     0          48 87.50000 10.172466 6.029851  0   0
- 8:     0     1     0     0          47 85.10638  8.940702 6.189774  0   0
- 9:     1     1     0     0          52 86.53846  8.617395 6.125121  0   0
-10:     0     1     0     0          50 90.00000  9.608849 6.109503  0   0
-11:     0     1     1     0          51 94.11765  9.400248 6.018759  0   0
-12:     1     1     0     0          51 86.27451  9.162558 6.108449  0   0
-13:     0     1     1     0          49 95.91837  8.995233 6.149011  0   0
-14:     1     1     0     0          48 91.66667 10.391898 6.015907  0   0
-15:     1     0     0     0          48 87.50000  9.136762 6.121580  0   0
-      Dlag50 t50.total t50.Germinated     TMGR      AUC      MGT Skewness
- 1: 6.034954  6.355122       6.034954 5.912195 1108.975 6.632252 1.098973
- 2: 6.175193  6.473490       6.175193 6.031282 1128.559 6.784407 1.098655
- 3: 6.138110  6.244190       6.138110 5.938179 1283.693 6.772742 1.103392
- 4: 6.125172  6.276793       6.125172 5.972686 1239.887 6.739665 1.100323
- 5: 6.049641  6.103433       6.049641 5.914289 1328.328 6.654980 1.100062
- 6: 6.097412  6.182276       6.097412 5.961877 1294.463 6.702470 1.099232
- 7: 6.029851  6.202812       6.029851 5.914057 1213.908 6.622417 1.098272
- 8: 6.189774  6.439510       6.189774 6.036193 1164.346 6.804000 1.099232
- 9: 6.125121  6.352172       6.125121 5.961631 1188.793 6.745241 1.101242
-10: 6.109503  6.253042       6.109503 5.978115 1240.227 6.711899 1.098600
-11: 6.018759  6.099434       6.018759 5.883558 1305.200 6.624247 1.100600
-12: 6.108449  6.326181       6.108449 5.964079 1188.021 6.718636 1.099892
-13: 6.149011  6.207500       6.149011 5.998270 1316.407 6.762272 1.099733
-14: 6.015907  6.122385       6.015907 5.905179 1273.386 6.604963 1.097916
-15: 6.121580  6.317392       6.121580 5.976088 1203.664 6.732267 1.099760
-                                                             msg isConv
- 1: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 2: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 3: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 4: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 5: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 6: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 7: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 8: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
- 9: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
-10: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
-11: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
-12: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
-13: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
-14: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
-15: #1. Relative error in the sum of squares is at most `ftol'.    TRUE
-    txp.total_10 txp.total_60 Uniformity_90 Uniformity_10 Uniformity
- 1:     4.956266     6.744598      7.537688      4.831809   2.705880
- 2:     4.983236     6.872603      7.835407      4.866755   2.968652
- 3:     4.673022     6.608437      8.137340      4.630062   3.507277
- 4:     4.850876     6.614967      7.834806      4.788598   3.046208
- 5:     4.814126     6.386788      7.639025      4.790947   2.848078
- 6:     4.868635     6.477594      7.693458      4.832474   2.860984
- 7:     4.930423     6.510495      7.483642      4.858477   2.625165
- 8:     4.940058     6.823299      7.914162      4.841106   3.073056
- 9:     4.836659     6.733275      7.904040      4.746574   3.157466
-10:     4.920629     6.566505      7.679176      4.860681   2.818494
-11:     4.798630     6.391288      7.603603      4.764249   2.839354
-12:     4.893597     6.684521      7.763844      4.806015   2.957830
-13:     4.841310     6.509952      7.850339      4.816395   3.033943
-14:     4.915143     6.397486      7.432360      4.869401   2.562960
-15:     4.892505     6.667247      7.785804      4.813086   2.972718

+
## No test: 
+##D data(gcdata)
+##D 
+##D counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05",
+##D                           "Day06", "Day07", "Day08", "Day09", "Day10",
+##D                           "Day11", "Day12", "Day13", "Day14")
+##D 
+##D FourPHFfit.bulk(gcdata, total.seeds.col = "Total Seeds",
+##D                     counts.intervals.cols = counts.per.intervals,
+##D                     intervals = 1:14, partial = TRUE,
+##D                     fix.y0 = TRUE, fix.a = TRUE, xp = c(10, 60),
+##D                     tmax = 20, tries = 3, umax = 90, umin = 10)
+## End(No test)

 

 

 

@@ -1781,19 +2055,22 @@ 

 

 

 Session Info

-
-
R version 4.0.0 (2020-04-24)
-Platform: x86_64-w64-mingw32/x64 (64-bit)
-Running under: Windows 10 x64 (build 17763)
+
+
R version 4.0.1 (2020-06-06)
+Platform: x86_64-pc-linux-gnu (64-bit)
+Running under: Ubuntu 18.04.4 LTS
 
 Matrix products: default
+BLAS:   /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3
+LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3
 
 locale:
-[1] LC_COLLATE=English_United States.1252 
-[2] LC_CTYPE=English_United States.1252   
-[3] LC_MONETARY=English_United States.1252
-[4] LC_NUMERIC=C                          
-[5] LC_TIME=English_United States.1252    
+ [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+ [3] LC_TIME=en_IN.UTF-8        LC_COLLATE=en_US.UTF-8    
+ [5] LC_MONETARY=en_IN.UTF-8    LC_MESSAGES=en_US.UTF-8   
+ [7] LC_PAPER=en_IN.UTF-8       LC_NAME=C                 
+ [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+[11] LC_MEASUREMENT=en_IN.UTF-8 LC_IDENTIFICATION=C       
 
 attached base packages:
 [1] stats     graphics  grDevices utils     datasets  methods   base     
@@ -1803,29 +2080,227 @@ 

 
 loaded via a namespace (and not attached):
  [1] minpack.lm_1.2-1  tidyselect_1.1.0  xfun_0.14         pander_0.6.3     
- [5] purrr_0.3.4       lattice_0.20-41   colorspace_1.4-1  vctrs_0.3.0      
+ [5] purrr_0.3.4       lattice_0.20-41   colorspace_1.4-1  vctrs_0.3.1      
  [9] generics_0.0.2    htmltools_0.4.0   yaml_2.2.1        XML_3.99-0.3     
 [13] rlang_0.4.6       pkgdown_1.5.1     pillar_1.4.4      glue_1.4.1       
 [17] lifecycle_0.2.0   plyr_1.8.6        stringr_1.4.0     munsell_0.5.0    
-[21] gtable_0.3.0      memoise_1.1.0     evaluate_0.14     labeling_0.3     
-[25] knitr_1.28        gbRd_0.4-11       curl_4.3          highr_0.8        
-[29] broom_0.5.6       Rcpp_1.0.4.6      scales_1.1.1      backports_1.1.6  
-[33] desc_1.2.0        farver_2.0.3      fs_1.4.1          ggplot2_3.3.0    
-[37] digest_0.6.25     stringi_1.4.6     dplyr_1.0.0       ggrepel_0.8.2    
-[41] grid_4.0.0        rprojroot_1.3-2   bibtex_0.4.2.2    mathjaxr_1.0-0   
-[45] Rdpack_0.11-2     tools_4.0.0       bitops_1.0-6      magrittr_1.5     
-[49] RCurl_1.98-1.2    tibble_3.0.1      crayon_1.3.4      tidyr_1.1.0      
-[53] pkgconfig_2.0.3   MASS_7.3-51.6     ellipsis_0.3.1    data.table_1.12.8
-[57] assertthat_0.2.1  rmarkdown_2.1     httr_1.4.1        rstudioapi_0.11  
-[61] R6_2.4.1          nlme_3.1-147      compiler_4.0.0   

+[21] gtable_0.3.0      memoise_1.1.0     evaluate_0.14     knitr_1.28       
+[25] gbRd_0.4-11       curl_4.3          highr_0.8         broom_0.5.6      
+[29] Rcpp_1.0.4.6      scales_1.1.1      backports_1.1.7   desc_1.2.0       
+[33] fs_1.4.1          ggplot2_3.3.1     digest_0.6.25     stringi_1.4.6    
+[37] dplyr_1.0.0       ggrepel_0.8.2     grid_4.0.1        rprojroot_1.3-2  
+[41] bibtex_0.4.2.2    mathjaxr_0.8-3    Rdpack_0.11-1     tools_4.0.1      
+[45] bitops_1.0-6      magrittr_1.5      RCurl_1.98-1.2    tibble_3.0.1     
+[49] crayon_1.3.4      tidyr_1.1.0       pkgconfig_2.0.3   MASS_7.3-51.6    
+[53] ellipsis_0.3.1    data.table_1.12.8 assertthat_0.2.1  rmarkdown_2.2    
+[57] httr_1.4.1        rstudioapi_0.11   R6_2.4.1          nlme_3.1-147     
+[61] compiler_4.0.1   

 

 

 

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diff --git a/docs/index.html b/docs/index.html
index bb977f5..fc5dace 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -124,7 +124,7 @@ 

 

 
ICAR-National Bureau of Plant Genetic Resources, New Delhi

 

-
minimal R version License: GPL v3 CRAN_Status_Badge rstudio mirror downloads  develVersion  Project Status: Active lifecycle Last-changedate Rdoc Zenodo DOI Analytics

+
minimal R version License: GPL v3 CRAN_Status_Badge rstudio mirror downloads  develVersion  Project Status: Active lifecycle Last-changedate Rdoc Zenodo DOI Analytics

 

 

 

@@ -172,8 +172,8 @@ 

 

 To cite the R package 'germinationmetrics' in publications use:
 
-  Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S. R., and Kalyani Srinivasan (2020).  germinationmetrics:
-  Seed Germination Indices and Curve Fitting. R package version 0.1.4,
+  Aravind, J., Vimala Devi, S., Radhamani, J., Jacob, S. R., and Kalyani Srinivasan (2020).  germinationmetrics: Seed
+  Germination Indices and Curve Fitting. R package version 0.1.4,
   https://github.com/aravind-j/germinationmetricshttps://cran.r-project.org/package=germinationmetrics.
 
 A BibTeX entry for LaTeX users is
@@ -187,8 +187,8 @@ 

     note = {https://cran.r-project.org/package=germinationmetrics},
   }
 
-This free and open-source software implements academic research by the authors and co-workers. If you use it, please
-support the project by citing the package.

+This free and open-source software implements academic research by the authors and co-workers. If you use it, please support
+the project by citing the package.

 

 
   

diff --git a/docs/news/index.html b/docs/news/index.html
index bacc5d1..ab0ed7e 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -200,6 +200,8 @@ 

 
  • Error in case of non-uniform intervals converted to warning.
    • 
 
  • Fixed documentation errors in FourPHFfit and CVGermTime.
    • 
 
  • Updated documentation for GermSpeed, GermSpeedAccumulated, CUGerm MeanGermRate, SEGermRate, CVG, MeanGermTime, VarGermTime, SEGermTime, GermUncertainty, GermSynchrony, MeanGermPercent, MeanGermNumber, WeightGermPercent, TimsonsIndex, GermRateGeorge and GermSynchrony.
    • 
+
  • Converted all equations in Rd files to MathJaxusing mathjaxr
+
    • 
 
 
    
 
    
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 31db431..71fcec8 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -1,9 +1,9 @@
-pandoc: 2.7.2
+pandoc: 2.7.3
 pkgdown: 1.5.1
 pkgdown_sha: ~
 articles:
   Introduction: Introduction.html
-last_built: 2020-06-15T15:26Z
+last_built: 2020-06-16T06:31Z
 urls:
   reference: https://aravind-j.github.io/germinationmetrics//reference
   article: https://aravind-j.github.io/germinationmetrics//articles
diff --git a/docs/reference/FourPHFfit.bulk.html b/docs/reference/FourPHFfit.bulk.html
index 70ae241..77fbe08 100644
--- a/docs/reference/FourPHFfit.bulk.html
+++ b/docs/reference/FourPHFfit.bulk.html
@@ -266,6 +266,7 @@ 
    See a
 
     
    Examples
    
     
    
+# \donttest{
 data(gcdata)
 
 counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05",
@@ -355,7 +356,8 @@ 
    Examp
 #> 12:     4.893597     6.684521      7.763844      4.806015   2.957830
 #> 13:     4.841310     6.509952      7.850339      4.816395   3.033943
 #> 14:     4.915143     6.397486      7.432360      4.869401   2.562960
-#> 15:     4.892505     6.667247      7.785804      4.813086   2.972718
    
+#> 15:     4.892505     6.667247      7.785804      4.813086   2.972718
    # }
+