vmsae: Variational Multivariate Spatial Small Area Estimation
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 + fileLICENSE |
| URL: | https://github.com/zhenhua-wang/vmsae |
| NeedsCompilation: | no |
| CRAN checks: | vmsae results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=vmsaeto link to this page.