The R Journal: accepted article

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msae: An R Package of Multivariate Fay Herriot Models for Small Area Estimation PDF download
Novia Permatasari and Azka Ubaidillah

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 Kb)
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


CC BY 4.0
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://journal.r-project.org/archive/2021/RJ-2021-096/index.html}
}