vmsae
0.1.2Variational Multivariate Spatial Small Area Estimation
Overview
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.
Install
Health
- OK2026-08-0413 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 40%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 8%
Downloads
Repository
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Repository practices
Checks run against github.com/zhenhua-wang/vmsae on 2026-08-03.
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Dependencies
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Code & Tests
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.2Latest
- 0.1.12025-06-21 · diff ↗
- 0.1.02025-05-09
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-05-09
- Total releases
- 3 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 1.3 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet