saeHB: Small Area Estimation using Hierarchical Bayesian Method

Provides several functions for area level of small area estimation using hierarchical Bayesian (HB) methods with several univariate distributions for variables of interest. The dataset that is used in every function is generated accordingly in the Example. The 'rjags' package is employed to obtain parameter estimates. Model-based estimators involve the HB estimators which include the mean and the variation of mean. For the reference, see Rao and Molina (2015) <doi:10.1002/9781118735855>.

Version:	0.2.2
Depends:	R (≥ 2.10)
Imports:	stringr, coda, rjags, stats, nimble, CARBayesdata, MASS, grDevices, graphics
Suggests:	knitr, rmarkdown
Published:	2023-11-08
Author:	Zaza Yuda Perwira [aut, cre], Azka Ubaidillah [aut], Ika Yuni Wulansari [aut]
Maintainer:	Zaza Yuda Perwira <zazaperwira at bps.go.id>
BugReports:	https://github.com/zazaperwira/saeHB/issues
License:	GPL-3
URL:	https://github.com/zazaperwira/saeHB
NeedsCompilation:	no
SystemRequirements:	JAGS (http://mcmc-jags.sourceforge.net)
Materials:	README
CRAN checks:	saeHB results

Documentation:

Reference manual:	saeHB.pdf
Vignettes:	saeHB_vignette

Downloads:

Package source:	saeHB_0.2.2.tar.gz
Windows binaries:	r-prerel: saeHB_0.2.2.zip, r-release: saeHB_0.2.2.zip, r-oldrel: saeHB_0.2.2.zip
macOS binaries:	r-prerel (arm64): saeHB_0.2.2.tgz, r-release (arm64): saeHB_0.2.2.tgz, r-oldrel (arm64): saeHB_0.2.2.tgz, r-prerel (x86_64): saeHB_0.2.2.tgz, r-release (x86_64): saeHB_0.2.2.tgz
Old sources:	saeHB archive

Linking:

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