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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 |
| Reference manual: | agfh.pdf |
| Vignettes: |
agfh Vignette |
| 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, r-oldrel (x86_64): agfh_0.2.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.