nlfh fits Bayesian Fay-Herriot models for area-level small area estimation.
The package works with direct estimates, known sampling variances, and
area-level covariates, returning posterior draws and summaries for latent
area quantities and model parameters.
Maintainer: Paul Parker paulparker@ucsc.edu
The main entry point is fit_fh(). It supports a formula interface for
specifying the response and covariates, and a matrix interface for workflows
that already construct design matrices. Fitted model objects provide compact
printing, posterior summaries via summary(), fitted area estimates via
fitted(), and retained MCMC draws via posterior_draws().
Available model families are:
method = "linear": the standard linear Fay-Herriot model.
method = "rnn": a random-weight neural network Fay-Herriot extension for
nonlinear mean functions. Non-intercept covariates are centered and scaled
by default, and the response is standardized internally before returned
quantities are transformed back to the original scale.
method = "bart": a BART Fay-Herriot model for flexible nonlinear and
interaction effects. The first model-matrix column is treated as a
baseline/intercept column and is excluded from BART variable importance.
Useful links: