Package: saeHB.ME 1.0.1

Muhammad Rifqi Mubarak

saeHB.ME: Small Area Estimation with Measurement Error using Hierarchical Bayesian Method

Implementation of small area estimation using Hierarchical Bayesian (HB) Method when auxiliary variable measured with error. The 'rjags' package is employed to obtain parameter estimates. For the references, see Rao and Molina (2015) <doi:10.1002/9781118735855>, Ybarra and Lohr (2008) <doi:10.1093/biomet/asn048>, and Ntzoufras (2009, ISBN-10: 1118210352).

Authors:Azka Ubaidillah [aut], Muhammad Rifqi Mubarak [aut, cre]

saeHB.ME_1.0.1.tar.gz
saeHB.ME_1.0.1.tar.gz(r-4.5-noble)saeHB.ME_1.0.1.tar.gz(r-4.4-noble)
saeHB.ME_1.0.1.tgz(r-4.4-emscripten)saeHB.ME_1.0.1.tgz(r-4.3-emscripten)
saeHB.ME.pdf |saeHB.ME.html✨
saeHB.ME/json (API)

# Install 'saeHB.ME' in R:
install.packages('saeHB.ME', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • dataHBME - Sample Data for Small Area Estimation with Measurement Error using Hierarchical Bayesian Method under Normal Distribution
  • dataTMEHB - Sample Data for Small Area Estimation with Measurement Error using Hierarchical Bayesian Method under Student-t Distribution

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

1.00 score 1 stars 127 downloads 2 exports 11 dependencies

Last updated 1 years agofrom:601337c689. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 13 2024
R-4.5-linuxOKDec 13 2024

Exports:meHBNormalmeHBt

Dependencies:clicodagluelatticelifecyclemagrittrrjagsrlangstringistringrvctrs