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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.2 |
rolling linux/jammy R-4.5 | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
rolling linux/noble R-4.5 | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
rolling source/ R- | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
latest linux/jammy R-4.5 | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
latest linux/noble R-4.5 | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
latest source/ R- | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
2026-04-26 source/ R- | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
2026-04-23 source/ R- | vmsae_0.1.2.tar.gz |
1.3 MiB |
0.1.2 |
2026-04-09 windows/windows R-4.5 | vmsae_0.1.2.zip |
1.3 MiB |