Package: msae
Type: Package
Title: Multivariate Fay Herriot Models for Small Area Estimation
Version: 0.1.5
Author: Novia Permatasari, Azka Ubaidillah
Maintainer: Novia Permatasari <novia.permatasari@bps.go.id>
Description: Implements multivariate Fay-Herriot models for small area
        estimation. It uses empirical best linear unbiased prediction
        (EBLUP) estimator. Multivariate models consider the correlation
        of several target variables and borrow strength from auxiliary
        variables to improve the effectiveness of a domain sample size.
        Models which accommodated by this package are univariate model
        with several target variables (model 0), multivariate model
        (model 1), autoregressive multivariate model (model 2), and
        heteroscedastic autoregressive multivariate model (model 3).
        Functions provide EBLUP estimators and mean squared error (MSE)
        estimator for each model. These models were developed by
        Roberto Benavent and Domingo Morales (2015)
        <doi:10.1016/j.csda.2015.07.013>.
License: GPL-2
LazyData: TRUE
Encoding: UTF-8
Depends: R (>= 2.10)
Imports: magic
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2026-09-26 08:25:26 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2022-04-24 18:30:02 UTC
RemoteUrl: https://github.com/cran/msae
RemoteRef: HEAD
RemoteSha: 418d7793ab36ea19cc3da3a653c4740d808585c8
Built: R 4.6.0; ; 2026-09-26 08:27:16 UTC; unix
