Rdta: Data Transforming Augmentation for Linear Mixed Models

We provide a toolbox to fit univariate and multivariate linear mixed models via data transforming augmentation. Users can also fit these models via typical data augmentation for a comparison. It returns either maximum likelihood estimates of unknown model parameters (hyper-parameters) via an EM algorithm or posterior samples of those parameters via MCMC. Also see Tak et al. (2019) <doi:10.1080/10618600.2019.1704295>.

Version: 1.0.1
Depends: R (≥ 2.2.0)
Imports: MCMCpack (≥ 1.4-4), mvtnorm (≥ 1.0-11), Rdpack, stats
Published: 2024-01-27
DOI: 10.32614/CRAN.package.Rdta
Author: Hyungsuk Tak, Kisung You, Sujit K. Ghosh, and Bingyue Su
Maintainer: Hyungsuk Tak <hyungsuk.tak at gmail.com>
License: GPL-2
NeedsCompilation: no
CRAN checks: Rdta results


Reference manual: Rdta.pdf


Package source: Rdta_1.0.1.tar.gz
Windows binaries: r-devel: Rdta_1.0.1.zip, r-release: Rdta_1.0.1.zip, r-oldrel: Rdta_1.0.1.zip
macOS binaries: r-release (arm64): Rdta_1.0.1.tgz, r-oldrel (arm64): Rdta_1.0.1.tgz, r-release (x86_64): Rdta_1.0.1.tgz, r-oldrel (x86_64): Rdta_1.0.1.tgz
Old sources: Rdta archive


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