The R Journal: article published in 2021, volume 13:2

msae: An R Package of Multivariate Fay-Herriot Models for Small Area Estimation
Novia Permatasari and Azka Ubaidillah , The R Journal (2021) 13:2, pages 111-122.

Abstract 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.

Received: 2020-05-01; online 2021-11-15, supplementary material, (2.2 KiB)
CRAN packages: sae, rsae, nlme, hbsae, JoSAE, BayesSAE, mme, saery, msae
CRAN Task Views implied by cited CRAN packages: OfficialStatistics, Bayesian, ChemPhys, Econometrics, Environmetrics, Finance, Psychometrics, SocialSciences, Spatial, SpatioTemporal

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2021-096,
  author = {Novia Permatasari and Azka Ubaidillah},
  title = {{msae: An R Package of Multivariate Fay-Herriot Models for
          Small Area Estimation}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-096},
  url = {https://doi.org/10.32614/RJ-2021-096},
  pages = {111--122},
  volume = {13},
  number = {2}
}