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: 0.1.1 Depends: R (≥ 3.5.0) Imports: dplyr, ggplot2, gridExtra, sf, tidyr, reticulate, methods, rlang Published: 2025-06-21 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=vmsae to link to this page.
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