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Estimation of mean squared prediction error of a small area predictor is provided. In particular, the recent method of Simple, Unified, Monte-Carlo Assisted approach for the mean squared prediction error estimation of small area predictor is provided. We also provide other existing methods of mean squared prediction error estimation such as jackknife method for the mixed logistic model.
| Version: | 0.1.0 |
| Imports: | lme4, psych, stats |
| Published: | 2024-07-21 |
| DOI: | 10.32614/CRAN.package.SumcaVer1 |
| Author: | Mahmoud Torabi [aut, cre], Jiming Jiang [ctb] |
| Maintainer: | Mahmoud Torabi <mahmoud.torabi at umanitoba.ca> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | SumcaVer1 results |
| Reference manual: | SumcaVer1.pdf |
| Package source: | SumcaVer1_0.1.0.tar.gz |
| Windows binaries: | r-devel: SumcaVer1_0.1.0.zip, r-release: SumcaVer1_0.1.0.zip, r-oldrel: SumcaVer1_0.1.0.zip |
| macOS binaries: | r-release (arm64): SumcaVer1_0.1.0.tgz, r-oldrel (arm64): SumcaVer1_0.1.0.tgz, r-release (x86_64): SumcaVer1_0.1.0.tgz, r-oldrel (x86_64): SumcaVer1_0.1.0.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.