Package: vmsae
Title: Variational Multivariate Spatial Small Area Estimation
Version: 0.1.2
Maintainer: Zhenhua Wang <zhenhua.wang@missouri.edu>
Authors@R: c(
    person("Zhenhua", "Wang", email = "zhenhua.wang@missouri.edu", role = c("aut", "cre")),
    person("Paul A.", "Parker", email = "pparker1@ucsc.edu", role = c("aut", "res")),
    person("Scott H.", "Holan", email = "holans@missouri.edu", role = c("aut", "res")))
Description: Variational Autoencoded Multivariate Spatial Fay-Herriot models are designed to efficiently estimate population parameters in small area estimation. This package implements the variational generalized multivariate spatial Fay-Herriot model (VGMSFH) using 'NumPyro' and 'PyTorch' backends, as demonstrated by Wang, Parker, and Holan (2025) <doi:10.48550/arXiv.2503.14710>. The 'vmsae' package provides utility functions to load weights of the pretrained variational autoencoders (VAEs) as well as tools to train custom VAEs tailored to users specific applications.
Depends: R (>= 3.5.0)
Imports: dplyr, ggplot2, gridExtra, sf, tidyr, reticulate, methods,
        rlang
URL: https://github.com/zhenhua-wang/vmsae
BugReports: https://github.com/zhenhua-wang/vmsae/issues
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-10-08 22:54:58 UTC; zhenhua
Author: Zhenhua Wang [aut, cre],
  Paul A. Parker [aut, res],
  Scott H. Holan [aut, res]
Repository: CRAN
Date/Publication: 2025-10-08 23:10:02 UTC
Built: R 4.4.3; ; 2025-11-26 05:00:58 UTC; windows
