mcmcsae: Markov Chain Monte Carlo Small Area Estimation

Fit multi-level models with possibly correlated random effects using Markov Chain Monte Carlo simulation. Such models allow smoothing over space and time and are useful in, for example, small area estimation.

Version: 0.6.0
Depends: R (≥ 3.2.0)
Imports: Matrix (≥ 1.2.0), Rcpp (≥ 0.11.0), methods, GIGrvg, loo (≥ 2.0.0), matrixStats
LinkingTo: Rcpp, RcppEigen, Matrix, GIGrvg
Suggests: BayesLogit, lintools, splines, spdep, maptools, bayesplot, coda, parallel, testthat, roxygen2, knitr, rmarkdown, survey
Published: 2021-01-20
Author: Harm Jan Boonstra [aut, cre], Grzegorz Baltissen [ctb]
Maintainer: Harm Jan Boonstra <hjboonstra at>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: mcmcsae results


Reference manual: mcmcsae.pdf
Vignettes: Basic area-level model
Linear regression, prediction, and survey weighting
Basic unit-level models
Package source: mcmcsae_0.6.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: mcmcsae_0.6.0.tgz, r-oldrel: mcmcsae_0.6.0.tgz
Old sources: mcmcsae archive


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