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) . 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.


Reference manual

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install.packages("vmsae")

0.1.2 by Zhenhua Wang, a year ago


https://github.com/zhenhua-wang/vmsae


Report a bug at https://github.com/zhenhua-wang/vmsae/issues


Browse source code at https://github.com/cran/vmsae


Authors: Zhenhua Wang [aut, cre] , Paul A. Parker [aut, res] , Scott H. Holan [aut, res]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports dplyr, ggplot2, gridExtra, sf, tidyr, reticulate, methods, rlang


See at CRAN