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.
| Version: | 0.1.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | dplyr, ggplot2, gridExtra, sf, tidyr, reticulate, methods, rlang |
| Published: | 2025-10-08 |
| DOI: | 10.32614/CRAN.package.vmsae |
| Author: | Zhenhua Wang [aut, cre], Paul A. Parker [aut, res], Scott H. Holan [aut, res] |
| Maintainer: | Zhenhua Wang <zhenhua.wang at missouri.edu> |
| BugReports: | https://github.com/zhenhua-wang/vmsae/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/zhenhua-wang/vmsae |
| NeedsCompilation: | no |
| CRAN checks: | vmsae results |
| Reference manual: | vmsae.html , vmsae.pdf |
| Package source: | vmsae_0.1.2.tar.gz |
| Windows binaries: | r-devel: vmsae_0.1.2.zip, r-release: vmsae_0.1.2.zip, r-oldrel: vmsae_0.1.2.zip |
| macOS binaries: | r-release (arm64): vmsae_0.1.2.tgz, r-oldrel (arm64): vmsae_0.1.2.tgz, r-release (x86_64): vmsae_0.1.2.tgz, r-oldrel (x86_64): vmsae_0.1.2.tgz |
| Old sources: | vmsae archive |
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