Package: saeRobust 0.5.0

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.

Authors:Sebastian Warnholz [aut, cre]

saeRobust_0.5.0.tar.gz
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saeRobust_0.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
saeRobust/json (API)
NEWS

# Install 'saeRobust' in R:
install.packages('saeRobust', repos = c('https://wahani.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/wahani/saerobust/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

3.86 score 1 stars 2 packages 12 scripts 499 downloads 46 exports 62 dependencies

Last updated from:db45ed2702. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK206
linux-devel-x86_64OK212
source / vignettesOK284
linux-release-arm64OK202
linux-release-x86_64OK259
macos-release-arm64OK135
macos-release-x86_64OK326
macos-oldrel-arm64OK157
macos-oldrel-x86_64OK322
windows-develOK174
windows-releaseOK175
windows-oldrelOK189
wasm-releaseOK165

Exports:addAverageDampaddConstraintMaxaddConstraintMinaddCounteraddHistoryaddMaxIteraddStorageblandAltmanPlotbootbootstrapconvCritAbsoluteconvCritRelativecorAR1corSAR1corSAR1AR1fitGenericModelfitrfhfitrsfhfitrstfhfitrtfhfixedPointgetKmakeXYmatAmatAConstmatBmatBConstmatTracematTZmatTZ1matUmatWmatWbcmsenewtonRaphsonnewtonRaphsonFunctionpsiOneqqPlotrfhscoretestMatXtestResponsetestResponse0testRookupdatevariance

Dependencies:aoosassertthatbootbrewcachemcallrclassclassIntclicommonmarkcpp11DBIdeldirdesce1071evaluatefarverfastmapfsggplot2gluegtablehighrisobandKernSmoothknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemodulespbapplypkgbuildpkgloadprocessxproxypsR6RColorBrewerRcppRcppArmadillorlangroxygen2rprojroots2S7scalessfspspDataspdepunitsvctrsviridisLitewithrwkxfunxml2yaml

Notes on the fixed point framework

Rendered fromfixedPoint.Rmdusingknitr::rmarkdownon May 19 2026.

Last update: 2016-03-04
Started: 2015-04-10

Readme and manuals

Help Manual

Help pageTopics
Fit model on Bootstrap sampleboot boot,ANY,ANY,integerORnumeric-method boot,rfh,rfhVariance,NULL-method bootstrap
Correlation StructurecorAR1 corAR1-class corSAR1 corSAR1-class corSAR1AR1 corSAR1AR1-class
Fitting PreceduresfitGenericModel fitrfh fitrsfh fitrstfh fitrtfh rfh,numeric,matrixORMatrix,numeric,corAR1-method rfh,numeric,matrixORMatrix,numeric,corSAR1-method rfh,numeric,matrixORMatrix,numeric,corSAR1AR1-method rfh,numeric,matrixORMatrix,numeric,NULL-method
Fixed Point Algorithm InfrastructureaddAverageDamp addConstraintMax addConstraintMin addCounter addHistory addMaxIter addStorage convCritAbsolute convCritRelative fixedPoint newtonRaphson newtonRaphsonFunction
makeXYmakeXY
Matrix constructor functionsmatA matAConst matB matBConst matTrace matTZ matTZ1 matU matW matWbc
Compute the Mean Squared Error of an Estimatormse mse.fitrfh
PlotsblandAltmanPlot plot.mse.fitrfh plot.prediction.fitrfh plot.rfh qqPlot
psiOnegetK psiOne
Robust Fay Herriot Modelpredict.fitrfh rfh rfh,formula,data.frame,character,ANY-method
Compute values of robust score functionsscore
Construction of test datatestMatX testResponse testResponse0 testRook
Update a fitted objectupdate,fitrfh-method update,rfh-method
Construct variancevariance variance.fitrfh variance.fitrsfh variance.fitrstfh variance.fitrtfh weights.fitrfh