rsae: Robust Small Area Estimation

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 ORCID iD [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

Documentation:

Reference manual: rsae.pdf
Vignettes: Robust Estimation and Prediction Under the Unit-Level SAE Model

Downloads:

Package source: rsae_0.2.tar.gz
Windows binaries: r-devel: rsae_0.2.zip, r-release: rsae_0.1-5.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_0.1-5.tgz, r-oldrel (x86_64): rsae_0.1-5.tgz
Old sources: rsae archive

Reverse dependencies:

Reverse suggests: maSAE, spaMM

Linking:

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