Empirical best linear unbiased prediction (EBLUP) and robust prediction of the area-level means under the basic unit-level model. The model can be fitted by maximum likelihood or a (robust) M-estimator. Mean square prediction error is computed by a parametric bootstrap.
Version: | 0.2 |
Depends: | R (≥ 3.5.0) |
Imports: | stats, graphics |
Suggests: | knitr, rmarkdown, robustbase, nlme |
Published: | 2022-05-24 |
Author: | Tobias Schoch [aut, cre], Brent Richard [cph] (F77 code zeroin.f) |
Maintainer: | Tobias Schoch <tobias.schoch at fhnw.ch> |
BugReports: | https://github.com/tobiasschoch/rsae/issues |
License: | GPL-2 | GPL-3 | FreeBSD [expanded from: GPL (≥ 2) | FreeBSD] |
URL: | https://github.com/tobiasschoch/rsae |
NeedsCompilation: | yes |
Citation: | rsae citation info |
Materials: | NEWS |
In views: | OfficialStatistics |
CRAN checks: | rsae results |
Reference manual: | rsae.pdf |
Vignettes: |
Robust Estimation and Prediction Under the Unit-Level SAE Model |
Package source: | rsae_0.2.tar.gz |
Windows binaries: | r-devel: rsae_0.2.zip, r-release: rsae_0.2.zip, r-oldrel: rsae_0.2.zip |
macOS binaries: | r-release (arm64): rsae_0.2.tgz, r-oldrel (arm64): rsae_0.2.tgz, r-release (x86_64): rsae_0.2.tgz, r-oldrel (x86_64): rsae_0.2.tgz |
Old sources: | rsae archive |
Reverse suggests: | maSAE, spaMM |
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