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fastsae: Fast Implementation of Small Area Estimation Methods

Provides high-performance implementations of Small Area Estimation (SAE) methods leveraging C++ ('Rcpp', 'RcppArmadillo') and 'OpenMP' multi-threading. Supports standard area-level Fay-Herriot models (Fay and Herriot, 1979 <doi:10.1080/01621459.1979.10482505>), Spatial Fay-Herriot models (Pratesi and Salvati, 2008 <doi:10.1002/env.861>), Spatio-Temporal Fay-Herriot models (Marhuenda et al., 2013 <doi:10.1016/j.csda.2013.01.016>), and unit-level Battese-Harter-Fuller models (Battese et al., 1988 <doi:10.1080/01621459.1988.10478561>). Features include empirical best linear unbiased prediction (EBLUP), analytical and bootstrap Mean Squared Error (MSE) estimation, automatic handling of unsampled domains, and modern S3 diagnostic methods.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: cli, ggplot2, lme4, methods, Rcpp, rlang, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: doParallel, dplyr, emdi, foreach, MASS, parallel, sae, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-09-30
DOI: 10.32614/CRAN.package.fastsae (may not be active yet)
Author: Ridson Al Farizal P ORCID iD [aut, cre, cph], Azka Ubaidillah ORCID iD [aut]
Maintainer: Ridson Al Farizal P <alfrzlp at gmail.com>
BugReports: https://github.com/ridsonap/fastsae/issues
License: GPL (≥ 3)
URL: https://ridsonap.github.io/fastsae/, https://github.com/ridsonap/fastsae
NeedsCompilation: yes
Materials: README
CRAN checks: fastsae results

Documentation:

Reference manual: fastsae.html , fastsae.pdf
Vignettes: Performance & Scalability Benchmarks (source, R code)
Getting Started with fastsae (source, R code)
Spatial and Spatio-Temporal Models (source, R code)
Unit-Level Estimation with Battese-Harter-Fuller (source, R code)

Downloads:

Package source: fastsae_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): fastsae_0.1.0.tgz, r-oldrel (x86_64): fastsae_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=fastsae to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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