diff --git a/NAMESPACE b/NAMESPACE
index 135692d..fcc7d77 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -10,9 +10,8 @@ S3method(summary,NetSim)
 S3method(summary,PointSim)
 S3method(summary,spacejamr)
 export("%>%")
-export(APLNetwork)
+export(NetSim)
 export(PointSim)
-export(PowerLawNetwork)
 export(as.spacejamr)
 export(compare_networks)
 importFrom(magrittr,"%>%")
diff --git a/R/NetSim-helpers.R b/R/NetSim-helpers.R
new file mode 100644
index 0000000..2b5a733
--- /dev/null
+++ b/R/NetSim-helpers.R
@@ -0,0 +1,137 @@
+# Author: Darren Colby
+# Date: 8/31/2021
+# Purpose: To create spatial interaction functions for the NetSim class
+
+# Spatial interaction functions -------------------------------------------
+
+
+#' Standard power law function
+#'
+#' @description helper function to estimate tie probability using a standard
+#' power law
+#'
+#' @usage standard(dist, base_prob, scale, power)
+#'
+#' @details This function should not be called directly
+#'
+#' @param dist the distance between a pair of points
+#'
+#' @return A numeric object representing the proability of two nodes sharing a
+#' connection
+#'
+#' @author Darren Colby
+#' Email: dscolby17@@gmail.com
+#' @noRd
+standard <- function(dist, base_prob, scale, power) {
+
+    prob <- (base_prob / ((1 + (scale * dist)) ^ abs(power)))
+
+    return(prob)
+
+}
+
+
+
+#' Attenuated power law function
+#'
+#' @description helper function to estimate tie probability using an attenuated
+#' power law
+#'
+#' @usage attenuated(dist, base_prob, scale, power)
+#'
+#' @details This function should not be called directly
+#'
+#' @param dist the distance between a pair of points
+#'
+#' @return A numeric object representing the proability of two nodes sharing a
+#' connection
+#'
+#' @author Darren Colby
+#' Email: dscolby17@@gmail.com
+#' @noRd
+attenuated <- function(dist, base_prob, scale, power) {
+
+    prob <- (base_prob / (1 + (scale * dist) ^ abs(power)))
+
+
+    return(prob)
+
+}
+
+
+#' Arctangent probability law
+#'
+#' @description helper function to estimate tie probability using an arctangent
+#' probability law
+#'
+#' @usage arctan(dist, base_prob, scale, power)
+#'
+#' @details This function should not be called directly
+#'
+#' @param dist the distance between a pair of points
+#'
+#' @return A numeric object representing the proability of two nodes sharing a
+#' connection
+#'
+#' @author Darren Colby
+#' Email: dscolby17@@gmail.com
+#' @noRd
+arctan <- function(dist, base_prob, scale, power) {
+
+    prob <- base_prob * (1 - ((2 / pi) * atan((scale * dist))))
+
+    return(prob)
+
+}
+
+
+#' Exponential decay law
+#'
+#' @description helper function to estimate tie probability using an exponential
+#' decay law
+#'
+#' @usage decay(dist, base_prob, scale, power)
+#'
+#' @details This function should not be called directly
+#'
+#' @param dist the distance between a pair of points
+#'
+#' @return A numeric object representing the proability of two nodes sharing a
+#' connection
+#'
+#' @author Darren Colby
+#' Email: dscolby17@@gmail.com
+#' @noRd
+decay <- function(dist, base_prob, scale, power) {
+
+    prob <- base_prob / exp((dist * scale))
+
+    return(prob)
+
+}
+
+
+#' Logistic probability law
+#'
+#' @description helper function to estimate tie probability using a logistic
+#' probability law
+#'
+#' @usage logistic(dist, base_prob, scale, power)
+#'
+#' @details This function should not be called directly
+#'
+#' @param dist the distance between a pair of points
+#'
+#' @return A numeric object representing the proability of two nodes sharing a
+#' connection
+#'
+#' @author Darren Colby
+#' Email: dscolby17@@gmail.com
+#' @noRd
+logistic <- function(dist, base_prob, scale, power) {
+
+    prob <- (2 * base_prob) / (1 + (exp(dist * scale)))
+
+    return(prob)
+}
+
diff --git a/R/NetSim.R b/R/NetSim.R
index 0b12227..a057def 100644
--- a/R/NetSim.R
+++ b/R/NetSim.R
@@ -2,62 +2,46 @@
 # Date: 8/31/2021
 # Purpose: To simulate spatial Bernoulli networks
 
-# Contructor methods to simulate a standard power law network -------------
-
-
-# Validate input to a PowerLawNetwork constructor
-#
-# @description validates a spatial Bernoulli network using a standard power law
-#
-#
-# @details This function should not be called by the user
-#
-# @param point_sim a PointSim object
-# @param base_prob the theoretical probability that two nodes (points) with
-# distance 0 share a tie.
-# @param scale a coefficient to multiply the distance by.
-# @param threshold if two node exceed this probability, they will be coded as
-# having a tie.
-# @param power the exponent at which tie probability decays.
-#
-# @return An igraph object
-#
-# @author Darren Colby
-#    Email: dscolby17@gmail.com
-validate_PowerLawNetwork <- function(point_sim, base_prob = 0.9, scale = 1,
-                                     threshold = 0.5, power = -2.8) {
+# Constructor methods to simulate a standard power law network ------------
 
-    # Ensures proper input
-    stopifnot(methods::is(point_sim, "PointSim"))
-
-
-    # Helper function to estimate the probability of a tie with given parameters
-    ProbabilityFunction <- function(dist) {
-
-        prob <- (base_prob/((1 + (scale * dist)) ^ abs(power)))
-
-        return(prob)
-
-    }
-
-
-    # Helper function to create ties if tie probability exceeds the threshold
-    ThresholdFunction <- function(prob) {
-
-        ifelse(prob > threshold, 1, 0)
 
-    }
+#' Validate input to a NetSim constructor
+#'
+#' @description validates a spatial Bernoulli network
+#'
+#' @usage validate_NetSim(point_sm, sif, base_prob, scale, threshold, power)
+#'
+#' @details This function should not be called by the user
+#'
+#' @param point_sim a PointSim object
+#' @param sif the spatial interaction function to use
+#' @param base_prob the theoretical probability that two nodes (points) with
+#' distance 0 share a tie.
+#' @param scale a coefficient to multiply the distance by.
+#' @param threshold if two node exceed this probability, they will be coded as
+#' having a tie.
+#' @param power the exponent at which tie probability decays.
+#'
+#' @return An igraph object
+#'
+#' @author Darren Colby
+#' Email: dscolby17@gmail.com
+#' @noRd
+validate_NetSim <- function(point_sim, sif, base_prob, scale, threshold, power) {
 
+    # Ensures proper input
+    stopifnot(methods::is(point_sim, "PointSim"))
 
     # Calculate the distance between all pairs of nodes
     distances <- dplyr::as_tibble(spatstat.geom::pairdist(point_sim),
                                   column_name = c("V1", "V2")) %>%
 
     # Apply the power law function
-    dplyr::mutate(dplyr::across(.fns = ProbabilityFunction),
+    dplyr::mutate(dplyr::across(.fns = sif, base_prob = base_prob,
+                                scale = scale, power = power),
 
     # Code as a tie if the probability exceeds the given threshold
-    dplyr::across(.fns = ThresholdFunction)) %>%
+    dplyr::across(.fns = function(prob){ifelse(prob > threshold, 1, 0)})) %>%
 
     # This is just a good practice
     dplyr::ungroup() %>%
@@ -72,201 +56,57 @@ validate_PowerLawNetwork <- function(point_sim, base_prob = 0.9, scale = 1,
 }
 
 
-# Validate and set class attribute of input to the PowerLawNetwork constructor
-#
-# @description creates a spatial Bernoulli network using a standard power law
-#
-# @details This function should not be called by the user
-#
-# @param point_sim a PointSim object
-# @param base_prob the theoretical probability that two nodes (points) with
-# distance 0 share a tie.
-# @param scale a coefficient to multiply the distance by.
-# @param threshold if two node exceed this probability, they will be coded as
-# having a tie.
-# @param power the exponent at which tie probability decays.
-#
-# @return An igraph object
-#
-# @author Darren Colby
-# Email: dscolby17@gmail.com
-new_PowerLawNetwork <- function(point_sim, base_prob, scale, threshold, power) {
-
-    validated_network <- validate_PowerLawNetwork(point_sim, base_prob, scale,
-                                                  threshold, power)
-
-    validated_network <- structure(validated_network, class = c("NetSim",
-                                                                "igraph"))
-
-    return(validated_network)
-
-}
-
-
-#' Simulate a power law network
+#' Validate and set class attribute of input to the NetSim constructor
 #'
-#' @description Simulates a spatial Bernoulli network from a NetSim object
-#' using a standard power law function as the spatial interaction function.
+#' @description creates a spatial Bernoulli network using a standard power law
 #'
-#' @usage PowerLawNetwork(point_sim, base_prob, scale, threshold, power)
+#' @usage new_NetSim(point_sim, sif, base_prob, scale, threshold, power)
 #'
-#' @details The algorithm proceeds in three steps. First, it calculates the
-#' distance between simulated points from a PointSim object. Then it calculates
-#' the distance between all pairs of points. Finally, it uses a standard power
-#' law function to calculate that any two point share a tie. If the threshold is
-#' exceeded, a tie is created.
+#' @details This function should not be called by the user
 #'
 #' @param point_sim a PointSim object
+#' @param sif a spatial interaction function
 #' @param base_prob the theoretical probability that two nodes (points) with
-#' distance 0 share a tie. Default is 0.9.
-#' @param scale a coefficient to multiply the distance by. Default is 1.
+#' distance 0 share a tie.
+#' @param scale a coefficient to multiply the distance by.
 #' @param threshold if two node exceed this probability, they will be coded as
-#' having a tie. Default is 0.5.
-#' @param power the exponent at which tie probability decays. Default is -2.8.
-#'
-#' @return A network object of class 'igraph' that can be manipulated using the
-#' 'igraph' package.
-#'
-#' @example
-#' # Load spacejamr object
-#' data("RI")
+#' having a tie.
+#' @param power the exponent at which tie probability decays.
 #'
-#' ri_points <- PointSim(points = 10, window = RI, seed = 42)
-#' power_law <- PowerLawNetwork(ri_points, base_prob = 0.92, scale = 1,
-#'                              threshold = 0.5, power = -2.4)
+#' @return An object of classes 'NetSim' and 'igraph' that can be further
+#' manipulated with 'igraph' functions and methods
 #'
-#' @author Darren Colby \cr
-#' Email: dscolby17@@gmail.com
-#'
-#' @references Butts, Carter T. Spatial models of large-scale interpersonal
-#' networks. Dissertation. (2002).
-#' @export
-PowerLawNetwork <- function(point_sim, base_prob = 0.9, scale = 1,
-                            threshold = 0.5, power = -2.8) {
-
-    validated_network <- new_PowerLawNetwork(point_sim, base_prob, scale,
-                                             threshold, power)
-
-    return(validated_network)
-
-}
-
-
-# Attenuated power law network generator ----------------------------------
-
-
-# Validate inputs to an APLNetwork constructor
-#
-# @description validates a spatial Bernoulli network using an attenuated power
-# law
-#
-# @details This function should not be called by the user
-#
-# @param point_sim a PointSim object
-# @param base_prob the theoretical probability that two nodes (points) with
-# distance 0 share a tie.
-# @param scale a coefficient to multiply the distance by.
-# @param threshold if two node exceed this probability, they will be coded as
-# having a tie.
-# @param power the exponent at which tie probability decays.
-#
-# @return An igraph object
-#
-# @author Darren Colby
-#    Email: dscolby17@gmail.com
-validate_APLNetwork <- function(point_sim, base_prob, scale, threshold, power) {
-
-    stopifnot(methods::is(point_sim, "PointSim"))
-
-
-    # Helper function to estimate the probability of a tie with given parameters
-    ProbabilityFunction <- function(dist) {
-
-        # Attenuated power law
-        prob <- (base_prob / (1 + (scale * dist) ^ abs(power)))
-
-
-        return(prob)
-
-    }
-
-
-    # Helper function to create ties if tie probability exceeds the threshold
-    ThresholdFunction <- function(prob) {
+#' @author Darren Colby
+#' Email: dscolby17@gmail.com
+#' @noRd
+new_NetSim <- function(point_sim, sif, base_prob, scale, threshold, power) {
 
-        ifelse(prob > threshold, 1, 0)
+    validated_net <- validate_NetSim(point_sim, sif, base_prob, scale,
+                                     threshold, power)
 
-    }
+    validated_net <- structure(validated_net, class = c("NetSim", "igraph"))
 
-
-    # Calculate the distance between all pairs of nodes
-    distances <- dplyr::as_tibble(spatstat.geom::pairdist(point_sim),
-                                  column_name = c("V1", "V2")) %>%
-
-        # Apply the power law function
-        dplyr::mutate(dplyr::across(.fns = ProbabilityFunction),
-
-        # Code as a tie if the probability exceeds the given threshold
-        dplyr::across(.fns = ThresholdFunction)) %>%
-
-        # This is just a good practice
-        dplyr::ungroup() %>%
-        as.matrix()
-
-    simulated_network <- igraph::graph_from_adjacency_matrix(distances,
-                                                             mode = "undirected") %>%
-        igraph::simplify() # Removes self loops
-
-    return(simulated_network)
+    return(validated_net)
 
 }
 
 
-# Validate and set class attribute to input passed to APLNetwork
-#
-# @description creates a spatial Bernoulli network using an attenuated power law
-#
-# @details This function should not be called by the user
-#
-# @param point_sim a PointSim object
-# @param base_prob the theoretical probability that two nodes (points) with
-# distance 0 share a tie.
-# @param scale a coefficient to multiply the distance by.
-# @param threshold if two node exceed this probability, they will be coded as
-# having a tie.
-# @param power the exponent at which tie probability decays.
-#
-# @return An igraph object
-#
-# @author Darren Colby
-#    Email: dscolby17@gmail.com
-new_APLNetwork <- function(point_sim, base_prob, scale, threshold, power) {
-
-    validated_network <- validate_APLNetwork(point_sim, base_prob, scale,
-                                             threshold, power)
-
-    validated_network <- structure(validated_network, class = c("NetSim",
-                                                                "igraph"))
-
-    return(validated_network)
-
-}
-
-
-#' Simulate an attenuated power law network
+#' Simulate a network from a point process or sequence
 #'
 #' @description Simulates a spatial Bernoulli network from a NetSim object
-#' using an attenuated power law function as the spatial interaction function.
+#' using one of six probability law distributions.
 #'
-#' @usage APLNetwork(point_sim, base_prob, scale, threshold, power)
+#' @usage NetSim(point_sim, sif, base_prob, scale, threshold, power)
 #'
 #' @details The algorithm proceeds in three steps. First, it calculates the
 #' distance between simulated points from a PointSim object. Then it calculates
-#' the distance between all pairs of points. Finally, it uses an attenuated
-#' power law function to calculate that any two point share a tie. If the
+#' the distance between all pairs of points. Finally, it uses a spatial
+#' interaction function to calculate that any two point share a tie. If the
 #' threshold is exceeded, a tie is created.
 #'
 #' @param point_sim a PointSim object
+#' @param sif the spatial interaction function to use. Default is a standard
+#' power law function.
 #' @param base_prob the theoretical probability that two nodes (points) with
 #' distance 0 share a tie. Default is 0.9.
 #' @param scale a coefficient to multiply the distance by. Default is 1.
@@ -274,16 +114,16 @@ new_APLNetwork <- function(point_sim, base_prob, scale, threshold, power) {
 #' having a tie. Default is 0.5.
 #' @param power the exponent at which tie probability decays. Default is -2.8.
 #'
-#' @return A network object of class 'igraph' that can be manipulated using the
-#' 'igraph' package.
+#' @return A network object of class 'NetSim' and 'igraph' that can be
+#' manipulated using the igraph' package.
 #'
 #' @example
 #' # Load spacejamr object
 #' data("RI")
 #'
 #' ri_points <- PointSim(points = 10, window = RI, seed = 42)
-#' apl_points <- APLNetwork(ri_points, base_prob = 0.92, scale = 1,
-#'                          threshold = 0.5, power = -2.4)
+#' power_law <- NetSim(ri_points, base_prob = 0.92, scale = 1, threshold = 0.5,
+#'                     power = -2.4)
 #'
 #' @author Darren Colby \cr
 #' Email: dscolby17@@gmail.com
@@ -291,13 +131,13 @@ new_APLNetwork <- function(point_sim, base_prob, scale, threshold, power) {
 #' @references Butts, Carter T. Spatial models of large-scale interpersonal
 #' networks. Dissertation. (2002).
 #' @export
-APLNetwork <- function(point_sim, base_prob = 0.9, scale = 1,
-                       threshold = 0.5, power = -2.8) {
+NetSim <- function(point_sim, sif = standard, base_prob = 0.9, scale = 1,
+                   threshold = 0.5, power = -2.8) {
 
-    validated_network <- new_APLNetwork(point_sim, base_prob, scale, threshold,
-                                        power)
+    validated_net <- new_NetSim(point_sim, sif, base_prob, scale, threshold,
+                                power)
 
-    return(validated_network)
+    return(validated_net)
 
 }
 
@@ -310,6 +150,8 @@ APLNetwork <- function(point_sim, base_prob = 0.9, scale = 1,
 #' @description This can take either a PowerLawNetwork or APLNetwork object as
 #' input, both of which are chidren of the NetSim class.
 #'
+#' @usage plot(x)
+#'
 #' @details This method returns a ggraph object, which can be further refined
 #' using standard ggraph and ggplot facilities.
 #'
@@ -329,9 +171,9 @@ APLNetwork <- function(point_sim, base_prob = 0.9, scale = 1,
 #' data("RI")
 #'
 #' ri_points <- PointSim(points = 10, window = RI, seed = 42)
-#' apl_points <- APLNetwork(ri_points, base_prob = 0.92, scale = 1,
-#'                          threshold = 0.5, power = -2.4)
-#' plot(apl_points)
+#' spl_points <- NetSim(ri_points, base_prob = 0.92, scale = 1, threshold = 0.5,
+#'                      power = -2.4)
+#' plot(spl_points)
 #'
 #' @author Darren Colby \cr
 #' Email:dscolby17@@gmail.com
@@ -359,6 +201,8 @@ plot.NetSim <- function(x, y, ..., layout = "stress",
 #'
 #' @description Plots a NetSim object and returns a ggraph object
 #'
+#' @usage print(x)
+#'
 #' @param x a NetSim object
 #' @param ... ignored.
 #'
@@ -369,9 +213,9 @@ plot.NetSim <- function(x, y, ..., layout = "stress",
 #' data("RI")
 #'
 #' ri_points <- PointSim(points = 10, window = RI, seed = 42)
-#' apl_points <- APLNetwork(ri_points, base_prob = 0.92, scale = 1,
-#'                          threshold = 0.5, power = -2.4)
-#' print(apl_points)
+#' spl_points <- NetSim(ri_points, base_prob = 0.92, scale = 1, threshold = 0.5,
+#'                      power = -2.4)
+#' print(spl_points)
 #'
 #' @author Darren Colby \cr
 #' Email: dscolby17@@gmail.com
@@ -388,6 +232,8 @@ print.NetSim <- function(x, ...) {
 #'
 #' @description Prints a summary of a NetSim object
 #'
+#' @usage summary(object)
+#'
 #' @param object a NetSim object
 #' @param ... ignored.
 #'
@@ -398,9 +244,9 @@ print.NetSim <- function(x, ...) {
 #' data("RI")
 #'
 #' ri_points <- PointSim(points = 10, window = RI, seed = 42)
-#' apl_points <- APLNetwork(ri_points, base_prob = 0.92, scale = 1,
-#'                          threshold = 0.5, power = -2.4)
-#' summary(apl_points)
+#' spl_points <- NetSim(ri_points, base_prob = 0.92, scale = 1, threshold = 0.5,
+#'                      power = -2.4)
+#' summary(spl_points)
 #'
 #' @author Darren Colby \cr
 #' Email: dscolby17@@gmail.com
diff --git a/R/PointSim-helpers.R b/R/PointSim-helpers.R
index 89cd437..f22595b 100644
--- a/R/PointSim-helpers.R
+++ b/R/PointSim-helpers.R
@@ -21,7 +21,7 @@
 #' simulated points
 #'
 #' @author Darren Colby
-#' Email: dscolby17@gmail.com
+#' Email: dscolby17@@gmail.com
 #' @noRd
 poisson_process <- function(n, win) {
 
@@ -48,7 +48,7 @@ poisson_process <- function(n, win) {
 #' contains simulated points
 #'
 #' @author Darren Colby
-#' Email: dscolby17@gmail.com
+#' Email: dscolby17@@gmail.com
 #' @noRd
 halton <- function(n, win) {
 
diff --git a/man/APLNetwork.Rd b/man/NetSim.Rd
similarity index 64%
rename from man/APLNetwork.Rd
rename to man/NetSim.Rd
index 154c917..da22222 100644
--- a/man/APLNetwork.Rd
+++ b/man/NetSim.Rd
@@ -1,14 +1,17 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/NetSim.R
-\name{APLNetwork}
-\alias{APLNetwork}
-\title{Simulate an attenuated power law network}
+\name{NetSim}
+\alias{NetSim}
+\title{Simulate a network from a point process or sequence}
 \usage{
-APLNetwork(point_sim, base_prob, scale, threshold, power)
+NetSim(point_sim, sif, base_prob, scale, threshold, power)
 }
 \arguments{
 \item{point_sim}{a PointSim object}
 
+\item{sif}{the spatial interaction function to use. Default is a standard
+power law function.}
+
 \item{base_prob}{the theoretical probability that two nodes (points) with
 distance 0 share a tie. Default is 0.9.}
 
@@ -20,18 +23,18 @@ having a tie. Default is 0.5.}
 \item{power}{the exponent at which tie probability decays. Default is -2.8.}
 }
 \value{
-A network object of class 'igraph' that can be manipulated using the
-'igraph' package.
+A network object of class 'NetSim' and 'igraph' that can be
+manipulated using the igraph' package.
 }
 \description{
 Simulates a spatial Bernoulli network from a NetSim object
-using an attenuated power law function as the spatial interaction function.
+using one of six probability law distributions.
 }
 \details{
 The algorithm proceeds in three steps. First, it calculates the
 distance between simulated points from a PointSim object. Then it calculates
-the distance between all pairs of points. Finally, it uses an attenuated
-power law function to calculate that any two point share a tie. If the
+the distance between all pairs of points. Finally, it uses a spatial
+interaction function to calculate that any two point share a tie. If the
 threshold is exceeded, a tie is created.
 }
 \references{
diff --git a/man/PowerLawNetwork.Rd b/man/PowerLawNetwork.Rd
deleted file mode 100644
index b99db40..0000000
--- a/man/PowerLawNetwork.Rd
+++ /dev/null
@@ -1,44 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/NetSim.R
-\name{PowerLawNetwork}
-\alias{PowerLawNetwork}
-\title{Simulate a power law network}
-\usage{
-PowerLawNetwork(point_sim, base_prob, scale, threshold, power)
-}
-\arguments{
-\item{point_sim}{a PointSim object}
-
-\item{base_prob}{the theoretical probability that two nodes (points) with
-distance 0 share a tie. Default is 0.9.}
-
-\item{scale}{a coefficient to multiply the distance by. Default is 1.}
-
-\item{threshold}{if two node exceed this probability, they will be coded as
-having a tie. Default is 0.5.}
-
-\item{power}{the exponent at which tie probability decays. Default is -2.8.}
-}
-\value{
-A network object of class 'igraph' that can be manipulated using the
-'igraph' package.
-}
-\description{
-Simulates a spatial Bernoulli network from a NetSim object
-using a standard power law function as the spatial interaction function.
-}
-\details{
-The algorithm proceeds in three steps. First, it calculates the
-distance between simulated points from a PointSim object. Then it calculates
-the distance between all pairs of points. Finally, it uses a standard power
-law function to calculate that any two point share a tie. If the threshold is
-exceeded, a tie is created.
-}
-\references{
-Butts, Carter T. Spatial models of large-scale interpersonal
-networks. Dissertation. (2002).
-}
-\author{
-Darren Colby \cr
-Email: dscolby17@gmail.com
-}
diff --git a/man/plot.NetSim.Rd b/man/plot.NetSim.Rd
index 77b9a06..95e2fd2 100644
--- a/man/plot.NetSim.Rd
+++ b/man/plot.NetSim.Rd
@@ -4,15 +4,7 @@
 \alias{plot.NetSim}
 \title{Plot a simulated network from a NetSim object}
 \usage{
-\method{plot}{NetSim}(
-  x,
-  y,
-  ...,
-  layout = "stress",
-  title = "Network Simulation",
-  node_color = "red",
-  edge_color = "blue"
-)
+plot(x)
 }
 \arguments{
 \item{x}{a NetSim graph}
diff --git a/man/print.NetSim.Rd b/man/print.NetSim.Rd
index 7ab5bd2..d05840e 100644
--- a/man/print.NetSim.Rd
+++ b/man/print.NetSim.Rd
@@ -4,7 +4,7 @@
 \alias{print.NetSim}
 \title{Print information from a NetSim object}
 \usage{
-\method{print}{NetSim}(x, ...)
+print(x)
 }
 \arguments{
 \item{x}{a NetSim object}
diff --git a/man/summary.NetSim.Rd b/man/summary.NetSim.Rd
index 11280a3..81e7e7b 100644
--- a/man/summary.NetSim.Rd
+++ b/man/summary.NetSim.Rd
@@ -4,7 +4,7 @@
 \alias{summary.NetSim}
 \title{Summary of NetSim graphs}
 \usage{
-\method{summary}{NetSim}(object, ...)
+summary(object)
 }
 \arguments{
 \item{object}{a NetSim object}
diff --git a/tests/testthat/test-NetSim.R b/tests/testthat/test-NetSim.R
index c4f9fd3..be16cbe 100644
--- a/tests/testthat/test-NetSim.R
+++ b/tests/testthat/test-NetSim.R
@@ -3,10 +3,9 @@ library(spacejamr)
 # Data for tests
 path <- system.file("extdata", "points.rds", package ="spacejamr")
 points <- readRDS(path)
-pl <- PowerLawNetwork(points)
-apl <- APLNetwork(points)
+pl <- NetSim(points)
 
-test_that("we can create power law networks from a PointSim object", {
+test_that("we can simulate networks from a PointSim object", {
 
     # Ensures the correct class
     expect_identical(class(pl), c("NetSim", "igraph"))
@@ -16,12 +15,3 @@ test_that("we can create power law networks from a PointSim object", {
 
 })
 
-test_that("we can create attenuated power law networks from a PointSim object", {
-
-    # Ensures the correct class
-    expect_identical(class(apl), c("NetSim", "igraph"))
-
-    # Ensures the correct length
-    expect_equal(length(apl), 10)
-
-})
diff --git a/tests/testthat/test-compare.R b/tests/testthat/test-compare.R
index 8cdbe4c..fa86ab8 100644
--- a/tests/testthat/test-compare.R
+++ b/tests/testthat/test-compare.R
@@ -7,8 +7,8 @@ options(warn = -1)
 # Load data for the test
 data("RI")
 ri_points <- PointSim(3, RI)
-pl <- PowerLawNetwork(ri_points)
-apl <- APLNetwork(ri_points)
+pl <- NetSim(ri_points)
+apl <- NetSim(ri_points)
 
 test_that("we can compare summary statistics of two networks", {
 
diff --git a/tests/testthat/test-generics.R b/tests/testthat/test-generics.R
index c9409a6..476dff6 100644
--- a/tests/testthat/test-generics.R
+++ b/tests/testthat/test-generics.R
@@ -3,7 +3,7 @@ library(spacejamr)
 # Load data for the test
 data("RI")
 ri_points <- PointSim(3, RI)
-pl <- PowerLawNetwork(ri_points)
+pl <- NetSim(ri_points)
 
 test_that("we can plot objects created with the spacejamr package", {