We describe the R package sae for small area estimation. This package can be used to obtain model-based estimates for small areas based on a variety of models at the area and unit levels, along with basic direct and indirect estimates. Mean squared errors are estimated by analytical approximations in simple models and applying bootstrap procedures in more complex models. We describe the package functions and show how to use them through examples.
sae, nlme, MASS, survey, sampling, rsae, JoSae, hbsae, mme, saery, sae2
OfficialStatistics, SocialSciences, Econometrics, Environmetrics, Pharmacokinetics, Psychometrics, Bayesian, ChemPhys, Distributions, Finance, Multivariate, NumericalMathematics, Robust, Spatial, SpatioTemporal, Survival, TimeSeries
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For attribution, please cite this work as
Molina & Marhuenda, "The R Journal: sae: An R Package for Small Area Estimation", The R Journal, 2015
BibTeX citation
@article{RJ-2015-007,
author = {Molina, Isabel and Marhuenda, Yolanda},
title = {The R Journal: sae: An R Package for Small Area Estimation},
journal = {The R Journal},
year = {2015},
note = {https://doi.org/10.32614/RJ-2015-007},
doi = {10.32614/RJ-2015-007},
volume = {7},
issue = {1},
issn = {2073-4859},
pages = {81-98}
}