cran. See also theR-universe documentation.Package: saeHB 0.2.2
Zaza Yuda Perwira
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>.
Authors:
saeHB_0.2.2.tar.gz
saeHB_0.2.2.tar.gz(r-4.5-noble)saeHB_0.2.2.tar.gz(r-4.4-noble)
saeHB_0.2.2.tgz(r-4.4-emscripten)saeHB_0.2.2.tgz(r-4.3-emscripten)
saeHB.pdf |saeHB.html✨
saeHB/json (API)
| # Install 'saeHB' in R: |
| install.packages('saeHB', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/zazaperwira/saehb/issues
Last updated 1 years agofrom:e8c0f38272. Checks:1 OK, 1 NOTE. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 24 2025 |
| R-4.5-linux | NOTE | Feb 24 2025 |
Exports:BetaBinomialExponentialExponentialDoubleGammaLogisticLognormalNegativeBinomialNormalPoissonPoissonGammaStudent_tStudent_tncWeibull
Dependencies:CARBayesdataclassclassIntclicodacpp11DBIe1071glueigraphKernSmoothlatticelifecyclemagrittrMASSMatrixnimblenumDerivpkgconfigpracmaproxyR6Rcpprjagsrlangs2sfstringistringrunitsvctrswk
Citation
To cite package ‘saeHB’ in publications use:
Yuda Perwira Z, Ubaidillah A, Yuni Wulansari I (2023). saeHB: Small Area Estimation using Hierarchical Bayesian Method. R package version 0.2.2, https://CRAN.R-project.org/package=saeHB.
Corresponding BibTeX entry:
@Manual{,
title = {saeHB: Small Area Estimation using Hierarchical Bayesian
Method},
author = {Zaza {Yuda Perwira} and Azka Ubaidillah and Ika {Yuni
Wulansari}},
year = {2023},
note = {R package version 0.2.2},
url = {https://CRAN.R-project.org/package=saeHB},
}
Readme and manuals
saeHB
Provides several functions for area level of small area estimation using hierarchical Bayesian (HB) method with several univariate distributions for variable of interest. The dataset that used in every function is generated accordingly in the Example. The 'rjags' package is employed to obtain parameter estimates. Model-based estimators involves the HB estimators which include the mean and the variation of mean. For the reference, see Rao and Molina (2015).
References
- Rao, J.N.K & Molina. (2015). Small Area Estimation 2nd Edition. New York: John Wiley and Sons, Inc.