agfh: Agnostic Fay-Herriot Model for Small Area Statistics

Implements the Agnostic Fay-Herriot model, an extension of the traditional small area model. In place of normal sampling errors, the sampling error distribution is estimated with a Gaussian process to accommodate a broader class of distributions. This flexibility is most useful in the presence of bounded, multi-modal, or heavily skewed sampling errors.

Version: 0.2.1
Imports: ggplot2, goftest, ks, mvtnorm, stats
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-06-21
Author: Marten Thompson [aut, cre, cph], Snigdhansu Chatterjee [ctb, cph]
Maintainer: Marten Thompson <thom7058 at umn.edu>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: agfh results

Documentation:

Reference manual: agfh.pdf
Vignettes: agfh Vignette

Downloads:

Package source: agfh_0.2.1.tar.gz
Windows binaries: r-devel: agfh_0.2.1.zip, r-release: agfh_0.2.1.zip, r-oldrel: agfh_0.2.1.zip
macOS binaries: r-release (arm64): agfh_0.2.1.tgz, r-oldrel (arm64): agfh_0.2.1.tgz, r-release (x86_64): agfh_0.2.1.tgz

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