Hierarchical Bayesian Small Area Estimation
Description
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
MSEs, as well as some model selection measures. Additional
functions provide means to compute aggregate estimates and
MSEs, to minimally adjust the small area estimates to
benchmarks at a higher aggregation level, and to graphically
compare different sets of small area estimates.