hbsaems: Hierarchical Bayesian Area-Level Small Area Estimation Models

Fits area-level Hierarchical Bayesian Small Area Estimation models. The methodological foundation follows the standard area-level Small Area Estimation literature, primarily Rao and Molina (2015, ISBN: 9781118735787) <doi:10.1002/9781118735855>, while computational implementation is adapted to the parameterisation and prior-specification conventions of the 'brms' package <doi:10.18637/jss.v080.i01>, which targets the Stan back-end. Supports a principled Bayesian workflow <doi:10.48550/arXiv.2011.01808>, with prior predictive checks, convergence diagnostics, model comparison, spatial random effects, custom distributions, missing-data handling, and a bilingual 'shiny' application for non-programmer analysts.

Version:	1.1.0
Depends:	R (≥ 4.0.0)
Imports:	brms (≥ 2.18.0), coda (≥ 0.19-4), ggplot2 (≥ 3.3.5), mice (≥ 3.14.0), rstantools (≥ 2.4.0), stats, utils
Suggests:	bayesplot, bridgesampling, DT, energy, knitr (≥ 1.40), loo, mgcv, minerva, mockery, posterior, priorsense, readxl, rmarkdown (≥ 2.16), rstan, sf, shiny, shinydashboard (≥ 0.7.2), shinyWidgets, shinytest2, spdep, spelling (≥ 2.2), testthat (≥ 3.0.0)
Published:	2026-06-01
DOI:	10.32614/CRAN.package.hbsaems
Author:	Achmad Syahrul Choir [aut, cre], Saniyyah Sri Nurhayati [aut], Sofi Zamzanah [aut], Arsyka Laila Oktalia Siregar [aut]
Maintainer:	Achmad Syahrul Choir <madsyair at stis.ac.id>
BugReports:	https://github.com/madsyair/hbsaems/issues
License:	GPL (≥ 3)
URL:	https://madsyair.github.io/hbsaems/, https://github.com/madsyair/hbsaems
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	hbsaems results

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