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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/zazaperwira/saehb/issues
Last updated 1 years agofrom:e8c0f38272. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 02 2024 |
R-4.5-linux | NOTE | Dec 02 2024 |
Exports:BetaBinomialExponentialExponentialDoubleGammaLogisticLognormalNegativeBinomialNormalPoissonPoissonGammaStudent_tStudent_tncWeibull
Dependencies:CARBayesdataclassclassIntclicodacpp11DBIe1071glueigraphKernSmoothlatticelifecyclemagrittrMASSMatrixnimblenumDerivpkgconfigpracmaproxyR6Rcpprjagsrlangs2sfstringistringrunitsvctrswk