hbsae - Hierarchical Bayesian Small Area Estimation
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.
