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-x86_64)saeRobust_0.5.0.tgz(r-4.6-arm64)saeRobust_0.5.0.tgz(r-4.5-x86_64)saeRobust_0.5.0.tgz(r-4.5-arm64)
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saeRobust_0.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
saeRobust/json (API)

# 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:

openblas cpp

3.86 score 1 stars 2 packages 12 scripts 568 downloads 46 exports 63 dependencies

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

Target	Result	Time
linux-devel-arm64	OK	197
linux-devel-x86_64	OK	201
source / vignettes	OK	241
linux-release-arm64	OK	187
linux-release-x86_64	OK	208
macos-release-arm64	OK	154
macos-release-x86_64	OK	314
macos-oldrel-arm64	OK	207
macos-oldrel-x86_64	OK	319
windows-devel	OK	210
windows-release	OK	179
windows-oldrel	OK	177
wasm-release	OK	160

Exports:addAverageDamp addConstraintMax addConstraintMin addCounter addHistory addMaxIter addStorage blandAltmanPlot boot bootstrap convCritAbsolute convCritRelative corAR1 corSAR1 corSAR1AR1 fitGenericModel fitrfh fitrsfh fitrstfh fitrtfh fixedPoint getK makeXY matA matAConst matB matBConst matTrace matTZ matTZ1 matU matW matWbc mse newtonRaphson newtonRaphsonFunction psiOne qqPlot rfh score testMatX testResponse testResponse0 testRook update variance

Dependencies:aoos assertthat boot brew cachem callr class classInt cli commonmark cpp11 DBI deldir desc e1071 evaluate farver fastmap fs ggplot2 glue gtable highr isoband KernSmooth knitr labeling lattice lifecycle magrittr MASS Matrix memoise modules otel pbapply pkgbuild pkgload processx proxy ps R6 RColorBrewer Rcpp RcppArmadillo rlang roxygen2 rprojroot s2 S7 scales sf sp spData spdep units vctrs viridisLite withr wk xfun xml2 yaml

Notes on the fixed point framework

Square Root | Square root solved with Newton-Raphson

Rendered fromfixedPoint.Rmdusingknitr::rmarkdown

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

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Fit model on Bootstrap sample	boot boot,ANY,ANY,integerORnumeric-method boot,rfh,rfhVariance,NULL-method bootstrap
Correlation Structure	corAR1 corAR1-class corSAR1 corSAR1-class corSAR1AR1 corSAR1AR1-class
Fitting Precedures	fitGenericModel 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 Infrastructure	addAverageDamp addConstraintMax addConstraintMin addCounter addHistory addMaxIter addStorage convCritAbsolute convCritRelative fixedPoint newtonRaphson newtonRaphsonFunction
makeXY	makeXY
Matrix constructor functions	matA matAConst matB matBConst matTrace matTZ matTZ1 matU matW matWbc
Compute the Mean Squared Error of an Estimator	mse mse.fitrfh
Plots	blandAltmanPlot plot.mse.fitrfh plot.prediction.fitrfh plot.rfh qqPlot
psiOne	getK psiOne
Robust Fay Herriot Model	predict.fitrfh rfh rfh,formula,data.frame,character,ANY-method
Compute values of robust score functions	score
Construction of test data	testMatX testResponse testResponse0 testRook
Update a fitted object	update,fitrfh-method update,rfh-method
Construct variance	variance variance.fitrfh variance.fitrsfh variance.fitrstfh variance.fitrtfh weights.fitrfh