Package: hbsaems 1.1.0

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.

Authors:Achmad Syahrul Choir [aut, cre], Saniyyah Sri Nurhayati [aut], Sofi Zamzanah [aut], Arsyka Laila Oktalia Siregar [aut]

hbsaems_1.1.0.tar.gz
hbsaems_1.1.0.zip(r-4.7)hbsaems_1.1.0.zip(r-4.6)hbsaems_1.1.0.zip(r-4.5)
hbsaems_1.1.0.tgz(r-4.6-any)hbsaems_1.1.0.tgz(r-4.5-any)
hbsaems_1.1.0.tar.gz(r-4.7-any)hbsaems_1.1.0.tar.gz(r-4.6-any)
hbsaems_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
hbsaems/json (API)

# Install 'hbsaems' in R:

install.packages('hbsaems', repos = c('https://madsyair.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/madsyair/hbsaems/issues

Pkgdown/docs site:https://madsyair.github.io

Datasets:

adjacency_matrix_car - Province-level Adjacency Matrix
adjacency_matrix_car_regency - Regency-level Adjacency Matrix
data_betalogitnorm - Simulated Beta Logit-Normal Data
data_binlogitnorm - Simulated Binomial Logit-Normal Data
data_fhnorm - Simulated Fay-Herriot Normal Data
data_lnln - Simulated Lognormal-Lognormal Data
spatial_weight_sar - Spatial Weight Matrix for Simultaneous Autoregressive Models

On CRAN:

5.37 score 1 stars 58 scripts 479 downloads 72 exports 109 dependencies

Last updated from:21eff3ec5c. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	304
source / vignettes	OK	363
linux-release-x86_64	OK	280
macos-release-arm64	OK	194
macos-oldrel-arm64	OK	148
windows-devel	OK	210
windows-release	OK	187
windows-oldrel	OK	200
wasm-release	OK	223

Dependencies:abind backports bayesplot BH bit bit64 boot bridgesampling brms Brobdingnag broom callr checkmate cli clipr coda codetools cpp11 crayon desc digest distributional dplyr farver forcats foreach future future.apply generics ggplot2 ggridges glmnet globals glue gridExtra gtable haven hms inline isoband iterators jomo labeling lattice lifecycle listenv lme4 loo magrittr MASS Matrix matrixStats mgcv mice minqa mitml mvtnorm nleqslv nlme nloptr nnet numDeriv ordinal otel pan parallelly pillar pkgbuild pkgconfig plyr posterior prettyunits processx progress ps purrr QuickJSR R6 rbibutils RColorBrewer Rcpp RcppEigen RcppParallel Rdpack readr reformulas reshape2 rlang rpart rstan rstantools S7 scales shape StanHeaders stringi stringr survival tensorA tibble tidyr tidyselect tzdb ucminf utf8 vctrs viridisLite vroom withr

Complete Workflow with hbsaems 1.1.0

Rendered fromcomplete-workflow.Rmdusingknitr::rmarkdown

Last update: 2026-06-01
Started: 2026-05-15

Help page	Topics
Province-level Adjacency Matrix	adjacency_matrix_car
Regency-level Adjacency Matrix (Coarse Spatial Cluster)	adjacency_matrix_car_regency
Loglogistic as a Custom Distribution Family for brms	brms_custom_loglogistic
Shifted Loglogistic as a Custom Distribution Family for brms	brms_custom_shifted_loglogistic
Build a brms Custom Family + Stanvars Pair from a Single Spec	build_brms_custom_family
build_spatial_weight: Construct M for CAR / SAR models	build_spatial_weight
Inspect Data Before Fitting an HBSAE Model	check_data
Check Shiny App Dependencies	check_shiny_deps
Validate a Spatial Weight Matrix Against CAR/SAR Theory	check_spatial_weight
MCMC Convergence Diagnostics for Fitted HBMs	convergence_check
Simulated Beta Logit-Normal Data	data_betalogitnorm
Simulated Binomial Logit-Normal Data	data_binlogitnorm
Simulated Fay-Herriot Normal Data	data_fhnorm
Simulated Lognormal-Lognormal Data	data_lnln
Deprecated Functions	deprecated hbcc hbmc hbpc hbsae
Extract a Diagnostic Summary	diagnostic_summary
Inspect a Registered HBSAE Model Specification	get_hbsae_model
hbm: Hierarchical Bayesian Small Area Models	hbm
Small Area Estimation Under a Beta Likelihood (Logit-Normal Link)	hbm_betalogitnorm
Small Area Estimation under a Binomial Logit-Normal Model	hbm_binlogitnorm
Sampler Configuration for HBSAE Models	hbm_control
Return the Data Used to Fit an hbmfit	hbm_data
Fit a Flexible HBSAE Model with Any Registered Family	hbm_flex
Get Comprehensive Model Information	hbm_info
Small Area Estimation under a Lognormal-Lognormal Model	hbm_lnln
Nonlinear-Term Configuration for HBSAE Models	hbm_nonlinear
Prior Configuration for HBSAE Models	hbm_priors
Get Model Warnings	hbm_warnings
Model Inspection Helpers	hbm-info
User-Facing Helper to Build an hbmfit Object	hbmfit
The hbmfit S3 Class	hbmfit-class
Standard S3 Methods for hbmfit	hbmfit-methods
Test Whether a Fitted HBM Has Converged	is_converged
Test Whether an Object Belongs to an hbsaems Result Class	is-hbsaems is.hbcc_results is.hbmc_results is.hbmfit is.hbpc_results is.hbsae_results
Test Whether an Object Is an hbsaems Check Result	is.hbsaems_check
List Registered HBSAE Models	list_hbsae_models
Loglogistic Distribution Functions	dloglogistic loglogistic ploglogistic qloglogistic rloglogistic
Bayesian Model Averaging on Small-Area Estimates	model_average
Compare One or Two Fitted HBMs	model_compare
Compare Multiple Fitted HBMs	model_compare_all
Compare Fitted HBMs	model-compare
Plot a Fitted hbmfit Object	plot.hbmfit
Extract Posterior Draws as a Matrix	posterior_draws
Compute Credible Intervals for an hbmfit Object	posterior_interval posterior_interval.hbmfit
Comprehensive Posterior Summary	posterior_summary_hbm
Posterior and Prior Extraction Methods for hbmfit	posterior-methods
Prior Predictive Check for Fitted HBMs	prior_check
Extract Prior Draws	prior_draws prior_draws.hbmfit
Power-Scale Prior Sensitivity Diagnostics for Fitted HBMs	prior_sensitivity
Read the Stan Function Code for a Custom Distribution	read_stan_function
Register a brms Custom Family with the hbsaems Model Registry	register_hbsae_brms_custom
Register a Custom HBSAE Model	register_hbsae_model
run_sae_app: Interactive Small Area Estimation Application	run_sae_app
Aggregate Predictions from Multiple hbsae_results	sae_aggregate
Benchmark Small-Area Estimates to Known Totals	sae_benchmark
Filter SAE Predictions by a Logical Condition	sae_filter
Generate Small Area Estimates	sae_predict
Standardise SAE Predictions	sae_scale
Apply a Transformation to SAE Predictions	sae_transform
Shifted (3-Parameter) Loglogistic Distribution	dshifted_loglogistic pshifted_loglogistic qshifted_loglogistic rshifted_loglogistic shifted_loglogistic
Spatial Weight Matrix for Simultaneous Autoregressive Models	spatial_weight_sar
Generic Summary Method for hbsaems Check Results	summary.hbsaems_check
Translate a UI String for the Shiny SAE App	tr
List All Translation Keys (for a Reference Language)	tr_keys
List Available Languages	tr_langs
Update a Fitted HBM	update_hbm
Validate an hbmfit Object	validate_hbmfit

Package: hbsaems 1.1.0

hbsaems: Hierarchical Bayesian Area-Level Small Area Estimation Models

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Help Manual

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