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>.

Getting started

Package details

AuthorHyungsuk Tak, Kisung You, Sujit K. Ghosh, and Bingyue Su
MaintainerHyungsuk Tak <hyungsuk.tak@gmail.com>
Package repositoryView on CRAN
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Rdta documentation built on Jan. 24, 2020, 5:10 p.m.