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 a Markov chain Monte Carlo method. Also see Tak, You, Ghosh, Su, and Kelly (2019+) <doi:10.1080/10618600.2019.1704295> <arXiv:1911.02748>.

Version: 1.0.0
Depends: R (≥ 2.2.0)
Imports: MCMCpack (≥ 1.4-4), mvtnorm (≥ 1.0-11), Rdpack, stats
Published: 2020-01-24
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

Downloads:

Reference manual: Rdta.pdf
Package source: Rdta_1.0.0.tar.gz
Windows binaries: r-devel: Rdta_1.0.0.zip, r-devel-gcc8: Rdta_1.0.0.zip, r-release: Rdta_1.0.0.zip, r-oldrel: Rdta_1.0.0.zip
OS X binaries: r-release: Rdta_1.0.0.tgz, r-oldrel: Rdta_1.0.0.tgz

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