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hbsaems (version 0.1.1)

Hierarchical Bayes Small Area Estimation Model using 'Stan'

Description

Implementing Hierarchical Bayesian Small Area Estimation models using the 'brms' package as the computational backend. The modeling framework follows the methodological foundations described in area-level models. This package is designed to facilitate a principled Bayesian workflow, enabling users to conduct prior predictive checks, model fitting, posterior predictive checks, model comparison, and sensitivity analysis in a coherent and reproducible manner. It supports flexible model specifications via 'brms' and promotes transparency in model development, aligned with the recommendations of modern Bayesian data analysis practices, implementing methods described in Rao and Molina (2015) .

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Install

install.packages('hbsaems')

Monthly Downloads

129

Version

0.1.1

License

GPL (>= 3)

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Maintainer

Achmad Syahrul Choir

Last Published

July 18th, 2025

Functions in hbsaems (0.1.1)

hbm

hbm : Hierarchical Bayesian Small Area Models
print.hbmc_results

Print a summary for a model goodness of fit and prior sensitivity
hbm_betalogitnorm

Small Area Estimation using Hierarchical Bayesian under Beta Distribution
print.hbcc_results

Print a summary for a convergence check
summary.hbsae_results

Create a summary of a prediction result
update_hbm

update_hbm : Update a Hierarchical Bayesian Model (hbm) object
hbm_binlogitnorm

Small Area Estimation using Hierarchical Bayesian under Logit-Normal Model
run_sae_app

Launch the Shiny App for Small Area Estimation using Hierarchical Bayesian
hbm_lnln

Small Area Estimation using Hierarchical Bayesian under Lognormal Distribution
spatial_weight_sar

Spatial Weight for Simultaneous Autoregressive (SAR)
data_fhnorm

Simulated Fay-Herriot Normal Data (Area-Level)
print.hbmfit

Print a summary for a fitted model represented by a hbmfit object
print.hbsae_results

Print a summary for a prediction result
print.hbpc_results

Print a summary for a prior predictive check
summary.hbmfit

Create a summary of a fitted model represented by a hbmfit object
summary.hbpc_results

Create a summary of a prior predictive check
data_binlogitnorm

Simulated Binomial–Logit-Normal data (area-level)
hbcc

hbcc : Hierarchical Bayesian Convergence Checks
data_betalogitnorm

Simulation Data for Beta Logit Normal Model
adjacency_matrix_car

Adjacency Matrix for Conditional Autoregressive (CAR)
data_lnln

Simulation Data for Lognormal-Lognormal Model
hbmc

hbmc: Check Model Goodness of Fit and Prior Sensitivity
summary.hbcc_results

Create a summary of a convergence check
hbpc

hbpc : Hierarchical Bayesian Prior Predictive Checking
summary.hbmc_results

Create a summary of a model goodness of fit and prior sensitivity
hbsae

hbsae : Hierarchical Bayesian Small Area Estimation