DESCRIPTION

Package: bspme
Type: Package
Title: Bayesian Spatial Measurement Error Models
Version: 1.0.2
Authors@R: c(person("Changwoo", "Lee", role=c("aut", "cre"), email="c.lee@stat.tamu.edu"), person("Eun Sug", "Park", role = c("aut")))
Author: Changwoo Lee[aut, cre], Eun Sug Park[aut]
Maintainer: Changwoo Lee <c.lee@stat.tamu.edu>
Description: Scalable methods for fitting Bayesian linear and generalized linear models in the presence of spatial exposure measurement error. These models typically arise from a two-stage Bayesian analysis of environmental exposures and health outcomes. From a first-stage model, predictions of the covariate of interest (''exposure'') and their uncertainty information (typically contained in MCMC samples) are used to form a multivariate normal prior distribution for exposure in a second-stage regression model. This package also provides implementation of the methods used in Lee et al. (2024) <https://arxiv.org/abs/2401.00634>. 
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Imports: 
    BayesLogit,
    coda,
    fields,
    spam,
    GpGp
Depends: 
    Matrix,
    R (>= 2.10)
URL: https://changwoo-lee.github.io/bspme/
BugReports: https://github.com/changwoo-lee/bspme/issues
Suggests: 
    knitr,
    rmarkdown
VignetteBuilder: knitr