Hierarchical Bayesian Small Area Estimation
Compute aggregates of small area estimates and MSEs.
Benchmark small area estimates.
Compute area-level cross-validation measure for sae objects.
Compute small area estimates based on the basic area-level model.
Fit a linear model with random area effects and compute small area est...
Compute small area estimates based on the basic unit-level model.
Compute small area estimates based on the survey regression estimator.
Generate artificial dataset for demonstration and testing purposes.
A package for hierarchical Bayesian small area estimation.
Plot method for objects of class sae.
Plot method for objects of class weights.
Print method for objects of class sae.
S3 class for the fitted model and SAE outcomes.
Summary method for objects of class weights.
Compute unit weights underlying the small area estimates or their aggr...
Functions to compute small area estimates based on a basic area or unit-level model. The model is fit using restricted maximum likelihood, or in a hierarchical Bayesian way. In the latter case numerical integration is used to average over the posterior density for the between-area variance. The output includes the model fit, small area estimates and corresponding mean squared errors, as well as some model selection measures. Additional functions provide means to compute aggregate estimates and mean squared errors, to minimally adjust the small area estimates to benchmarks at a higher aggregation level, and to graphically compare different sets of small area estimates.