mcmcsae - Markov Chain Monte Carlo Small Area Estimation
Fit multi-level models with possibly correlated random effects using Markov Chain Monte Carlo simulation. Such models allow smoothing over space and time and are useful in, for example, small area estimation.
Last updated 2 months ago
cpp
2.78 score 8 scripts 279 downloadshbsae - 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.
Last updated 3 years ago
2.53 score 2 stars 2 dependents 28 scripts 431 downloads