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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.
Getting started
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Package details |
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| Author | Zhenhua Wang [aut, cre], Paul A. Parker [aut, res], Scott H. Holan [aut, res] |
| Maintainer | Zhenhua Wang <zhenhua.wang@missouri.edu> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| URL | https://github.com/zhenhua-wang/vmsae |
| Package repository | View on CRAN |
| Installation |
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