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.
assertthat, ggplot2, Matrix, magrittr, MASS, modules, memoise,
Rcpp, spdep
'NAMESPACE.R' 'RcppExports.R' 'bootstrap.R' 'correlation.R'
'fit.R' 'fixedPoint.R' 'helper.R' 'makeXY.R' 'mat.R'
'matModels.R' 'mse.R' 'plot.R' 'print.R' 'psiFunctions.R'
'rfh.R' 'robustEstimationEquations.R'
'robustObjectiveFunctions.R' 'testData.R' 'update.R'
'variance.R'

assertthat, ggplot2, Matrix, magrittr, MASS, modules, memoise,
pbapply, Rcpp, spdep
'NAMESPACE.R' 'RcppExports.R' 'bootstrap.R' 'check.R'
'correlation.R' 'fit.R' 'fixedPoint.R' 'helper.R' 'makeXY.R'
'mat.R' 'matModels.R' 'mse.R' 'plot.R' 'print.R'
'psiFunctions.R' 'rfh.R' 'robustEstimationEquations.R'
'robustObjectiveFunctions.R' 'testData.R' 'update.R'
'variance.R'

Simulation Tools for Small Area Estimation
c(person("Sebastian", "Warnholz", role = c("aut", "cre"),
email = "wahani@gmail.com"),
person("Timo", "Schmid", role = "aut",
email = "Timo.Schmid@fu-berlin.de"))
dplyr(>= 0.2), functional, ggplot2, grDevices, MASS, utils,
spdep, stats, parallelMap
Tools for the simulation of data in the context of small area
estimation. Combine all steps of your simulation - from data generation
over drawing samples to model fitting - in one object. This enables easy
modification and combination of different scenarios. You can store your
results in a folder or start the simulation in parallel.
Sebastian Warnholz [aut, cre],
Timo Schmid [aut]

dplyr (>= 0.2), functional, ggplot2, grDevices, MASS, utils,
spdep, stats, parallelMap, tibble

dplyr(>= 0.2), ggplot2, MASS, spdep, parallel

c(person("Sebastian", "Warnholz", role = c("aut", "cre"),
email = "Sebastian.Warnholz@fu-berlin.de"),
person("Timo", "Schmid", role = "aut",
email = "Timo.Schmid@fu-berlin.de"))
dplyr(>= 0.2), functional, ggplot2, MASS, spdep, parallelMap