Package: spBFA
Type: Package
Title: Spatial Bayesian Factor Analysis
Version: 1.0
Date: 2019-10-16
Authors@R: person("Samuel I.", "Berchuck", email = "sib2@duke.edu", role = c("aut", "cre"))
Description: Implements a spatial Bayesian non-parametric factor analysis model with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC). Spatial correlation is introduced in the columns of the factor loadings matrix using a Bayesian non-parametric prior, the probit stick-breaking process. Areal spatial data is modeled using a conditional autoregressive (CAR) prior and point-referenced spatial data is treated using a Gaussian process. The response variable can be modeled as Gaussian, probit, Tobit, or Binomial (using Polya-Gamma augmentation). Temporal correlation is introduced for the latent factors through a hierarchical structure and can be specified as exponential or first-order autoregressive. 
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: yes
Depends: R (>= 3.0.2)
Imports: graphics, grDevices, msm (>= 1.0.0), mvtnorm (>= 1.0-0),
        pgdraw (>= 1.0), Rcpp (>= 0.12.9), stats, utils
Suggests: coda, classInt, knitr, rmarkdown, womblR (>= 1.0.3)
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.500.0.0)
VignetteBuilder: knitr
Language: en-US
Packaged: 2019-10-25 13:28:07 UTC; sam
Author: Samuel I. Berchuck [aut, cre]
Maintainer: Samuel I. Berchuck <sib2@duke.edu>
Repository: CRAN
Date/Publication: 2019-10-30 17:00:05 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 07:12:09 UTC; windows
Archs: i386, x64
