The paper introduces an R Package of multivariate Fay-Herriot models for small area estimation named msae. This package implements four types of Fay-Herriot models, including univariate Fay-Herriot model (model 0), multivariate Fay-Herriot model (model 1), autoregressive multivariate Fay-Herriot model (model 2), and heteroskedastic autoregressive multivariate Fay-Herriot model (model 3). It also contains some datasets generated based on multivariate Fay-Herriot models. We describe and implement functions through various practical examples. Multivariate Fay-Herriot models produce a more efficient parameter estimation than direct estimation and univariate model.
sae, rsae, nlme, hbsae, JoSAE, BayesSAE, mme, saery, msae
OfficialStatistics, Bayesian, ChemPhys, Econometrics, Environmetrics, Finance, Psychometrics, SocialSciences, Spatial, SpatioTemporal
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For attribution, please cite this work as
Permatasari & Ubaidillah, "The R Journal: msae: An R Package of Multivariate Fay-Herriot Models for Small Area Estimation", The R Journal, 2021
BibTeX citation
@article{RJ-2021-096,
author = {Permatasari, Novia and Ubaidillah, Azka},
title = {The R Journal: msae: An R Package of Multivariate Fay-Herriot Models for Small Area Estimation},
journal = {The R Journal},
year = {2021},
note = {https://doi.org/10.32614/RJ-2021-096},
doi = {10.32614/RJ-2021-096},
volume = {13},
issue = {2},
issn = {2073-4859},
pages = {111-122}
}