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

Documentation:

Reference manual:

Rdta.pdf

Downloads:

Package source:	Rdta_1.0.0.tar.gz
Windows binaries:	r-devel: Rdta_1.0.0.zip, r-release: Rdta_1.0.0.zip, r-oldrel: Rdta_1.0.0.zip
macOS binaries:	r-release (arm64): Rdta_1.0.0.tgz, r-oldrel (arm64): Rdta_1.0.0.tgz, r-release (x86_64): Rdta_1.0.0.tgz, r-oldrel (x86_64): Rdta_1.0.0.tgz

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