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 |
| DOI: |
10.32614/CRAN.package.agfh |
| 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:
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