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Provides small area estimation for count data type and gives option whether to use covariates in the estimation or not. By implementing Empirical Bayes (EB) Poisson-Gamma model, each function returns EB estimators and mean squared error (MSE) estimators for each area. The EB estimators without covariates are obtained using the model proposed by Clayton & Kaldor (1987) <doi:10.2307/2532003>, the EB estimators with covariates are obtained using the model proposed by Wakefield (2006) <doi:10.1093/biostatistics/kxl008> and the MSE estimators are obtained using Jackknife method by Jiang et. al. (2002) <doi:10.1214/aos/1043351257>.
Version: | 0.1.0 |
Depends: | R (≥ 2.10) |
Imports: | COUNT (≥ 1.3.4), MASS, stats |
Published: | 2020-04-28 |
DOI: | 10.32614/CRAN.package.saeeb |
Author: | Rizki Ananda Fauziah, Ika Yuni Wulansari |
Maintainer: | Rizki Ananda Fauziah <rizkiananda133 at gmail.com> |
License: | GPL-2 |
NeedsCompilation: | no |
CRAN checks: | saeeb results |
Reference manual: | saeeb.pdf |
Package source: | saeeb_0.1.0.tar.gz |
Windows binaries: | r-devel: saeeb_0.1.0.zip, r-release: saeeb_0.1.0.zip, r-oldrel: saeeb_0.1.0.zip |
macOS binaries: | r-release (arm64): saeeb_0.1.0.tgz, r-oldrel (arm64): saeeb_0.1.0.tgz, r-release (x86_64): saeeb_0.1.0.tgz, r-oldrel (x86_64): saeeb_0.1.0.tgz |
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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.