BayesSAE: Bayesian Analysis of Small Area Estimation

Provides a variety of methods from Rao (2003, ISBN:0-471-41374-7) and some other research articles to deal with several specific small area area- level models in Bayesian framework. Models provided range from the basic Fay-Herriot model to its improvement such as You-Chapman models, unmatched models, spatial models and so on. Different types of priors for specific parameters could be chosen to obtain MCMC posterior draws. The main sampling function is written in C with GSL lab so as to facilitate the computation. Model internal checking and model comparison criteria are also involved.

Version: 1.0-2
Depends: Formula, coda, lattice
Published: 2018-04-20
Author: Chengchun Shi Developer [aut, cre]
Maintainer: Chengchun Shi Developer <cshi4 at ncsu.edu>
License: GPL-2
NeedsCompilation: yes
Materials: NEWS
In views: OfficialStatistics
CRAN checks: BayesSAE results

Documentation:

Reference manual: BayesSAE.pdf

Downloads:

Package source: BayesSAE_1.0-2.tar.gz
Windows binaries: r-devel: BayesSAE_1.0-2.zip, r-release: BayesSAE_1.0-2.zip, r-oldrel: BayesSAE_1.0-2.zip
macOS binaries: r-release (arm64): BayesSAE_1.0-2.tgz, r-oldrel (arm64): BayesSAE_1.0-2.tgz, r-release (x86_64): BayesSAE_1.0-2.tgz, r-oldrel (x86_64): BayesSAE_1.0-2.tgz
Old sources: BayesSAE archive

Linking:

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