msaeOB: Optimum Benchmarking for Multivariate Small Area Estimation

Implements multivariate optimum benchmarking small area estimation. This package provides optimum benchmarking estimation for univariate and multivariate small area estimation and its MSE. In fact, MSE estimators for optimum benchmark are not readily available, so resampling method that called parametric bootstrap is applied. The optimum benchmark model and parametric bootstrap in this package are based on the model proposed in small area estimation. J.N.K Rao and Isabel Molina (2015, ISBN: 978-1-118-73578-7).

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: magic, abind, Matrix, MASS, stats
Suggests: covr, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2022-03-14
Author: Muhammad Yasqi Imanda [aut, cre], Zenda Oka Briantiko [aut], Azka Ubaidillah [aut]
Maintainer: Muhammad Yasqi Imanda <221810403 at stis.ac.id>
BugReports: https://github.com/yas-q/msaeOB/issues
License: GPL-3
URL: https://github.com/yas-q/msaeOB
NeedsCompilation: no
Materials: README
CRAN checks: msaeOB results

Documentation:

Reference manual: msaeOB.pdf
Vignettes: Vignette_msaeOB

Downloads:

Package source: msaeOB_0.1.0.tar.gz
Windows binaries: r-devel: msaeOB_0.1.0.zip, r-release: msaeOB_0.1.0.zip, r-oldrel: msaeOB_0.1.0.zip
macOS binaries: r-release (arm64): msaeOB_0.1.0.tgz, r-release (x86_64): msaeOB_0.1.0.tgz, r-oldrel: msaeOB_0.1.0.tgz

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