Packaged: 2013-10-01 20:05:13 UTC; gregorymatthews

Collate: 'mixmapTest.R' 'mixmapPI.R' 'MixMAPclass.R' 'plot.MixMAP.R'
Packaged: 2014-03-10 21:06:10 UTC; gregorymatthews

Imports: methods, graphics, stats, utils, lme4
Description: A collection of functions to implement the MixMAP algorithm, which performs gene
Packaged: 2015-08-10 19:06:02 UTC; gregorymatthews

Title: Classification with Matrix Variate Normal and t Distributions
comment = "author of original lda and qda functions"),
email = "ripley@stats.ox.ac.uk", role = c("ctb","cph")),
Description: Provides sampling and density functions for matrix
variate normal, t, and inverted t distributions;  ML estimation for matrix
variate normal and t distributions using the EM algorithm,
including some restrictions on the parameters; and classification by linear and
quadratic discriminant analysis for matrix variate normal and t
distributions described in Thompson et al. (2019) <arXiv:1907.09565>.
Performs clustering with matrix variate normal and t mixture models.
Suggests: knitr, rmarkdown, testthat, covr, ggplot2, dplyr, magrittr,
B. D. Ripley author of original lda and qda functions [ctb, cph],
W. N. Venables author of original lda and qda functions [ctb, cph]

Author: Alexandra Kuznetsova, Per Bruun Brockhoff
Imports: numDeriv, Matrix, nlme, lme4, MASS, Hmisc
Description: Performs complete analysis of linear mixed effects models

Maintainer: Cassandro Davi Emer <cde@actisys.org>
Description: Simple tools to perform mixture optimization based on the 'desirability' package by Max Kuhn.
It also provides a plot routine using 'ggplot2' and 'patchwork'.

Title: A Random-Forest-Based Approach for Imputing Clustered Incomplete
Description: It offers random-forest-based functions to impute clustered
incomplete data. The package is tailored for but not limited to imputing
multitissue expression data, in which a gene's expression is measured on the
collected tissues of an individual but missing on the uncollected tissues.
Depends: doParallel, randomForest, lme4, foreach