saeRobust: Robust Small Area Estimation

Methods to fit robust alternatives to commonly used models used in Small Area Estimation. The methods here used are based on best linear unbiased predictions and linear mixed models. At this time available models include area level models incorporating spatial and temporal correlation in the random effects.

Version: 0.2.0
Depends: R (≥ 3.3.0), methods, aoos
Imports: assertthat, ggplot2, Matrix, magrittr, MASS, modules, memoise, pbapply, Rcpp, spdep
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, sae, saeSim, testthat
Published: 2018-03-27
Author: Sebastian Warnholz [aut, cre]
Maintainer: Sebastian Warnholz <Sebastian.Warnholz at fu-berlin.de>
BugReports: https://github.com/wahani/saeRobust/issues
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: NEWS
CRAN checks: saeRobust results

Downloads:

Reference manual: saeRobust.pdf
Vignettes: fixedPoint
Package source: saeRobust_0.2.0.tar.gz
Windows binaries: r-devel: saeRobust_0.2.0.zip, r-release: saeRobust_0.2.0.zip, r-oldrel: saeRobust_0.2.0.zip
macOS binaries: r-release: saeRobust_0.2.0.tgz, r-oldrel: saeRobust_0.2.0.tgz
Old sources: saeRobust archive

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