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: 0.5.0
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: 2020-09-01
Author: Harm Jan Boonstra [aut, cre], Grzegorz Baltissen [ctb]
Maintainer: Harm Jan Boonstra <hjboonstra at gmail.com>
License: GPL-3
NeedsCompilation: yes
CRAN checks: mcmcsae results

Downloads:

Reference manual: mcmcsae.pdf
Vignettes: Area-level models
Linear regression and linear weighting
Unit-level models
Package source: mcmcsae_0.5.0.tar.gz
Windows binaries: r-devel: mcmcsae_0.5.0.zip, r-release: mcmcsae_0.5.0.zip, r-oldrel: mcmcsae_0.5.0.zip
macOS binaries: r-release: mcmcsae_0.5.0.tgz, r-oldrel: mcmcsae_0.5.0.tgz

Linking:

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