covariance structures for random effects. In particular, the package is
suited to fit quantitative genetic mixed models, often referred to as
'animal models'. Implements the average information algorithm as the main
tool to maximize the restricted log-likelihood, but with other algorithms

Title: Adaptive Group-Regularized Logistic Elastic Net Regression
Maintainer: Magnus M. Münch <m.munch@vumc.nl>
Description: Allows the user to incorporate multiple sources of co-data
(e.g., 	previously obtained p-values, published gene lists, and annotation) in the	estimation of a logistic regression model to enhance predictive performance and 	feature selection, as described in Münch, Peeters, van der Vaart, and van de Wiel 	(2018) <arXiv:1805.00389>.
Imports: Rcpp (>= 0.12.14), glmnet, Iso, pROC
Packaged: 2018-07-28 16:45:07 UTC; magnusmunch

Title: Graphical Reporting for Clinical Trials
Imports: rms (>= 4.1-3), lattice, latticeExtra, Formula, survival
Description: The greport package contains many functions useful for
monitoring and reporting the results of clinical trials and other
experiments in which treatments are compared.  LaTeX is
used to typeset the resulting reports, recommended to be in the
context of knitr. The Hmisc and lattice packages are used by greport

Imports: rms (>= 4.3-1), lattice, latticeExtra, ggplot2, Formula,
Description: Contains many functions useful for
context of 'knitr'. The 'Hmisc', 'ggplot2', and 'lattice' packages are used

Imports: rms (>= 4.4-1), lattice, latticeExtra, ggplot2, Formula,

Imports: rms (>= 5.0-0), lattice, latticeExtra, ggplot2, Formula,

Author: Frank E Harrell Jr <fh@fharrell.com>

Title: Simple and Scalable Statistical Modelling in R
Authors@R: person("Nick", "Golding", role = c("aut", "cre"),
Description: Write statistical models in R and fit them by MCMC on CPUs and GPUs, using Google TensorFlow (see <https://goldingn.github.io/greta> for more information).
library; TensorFlow (>= 1.0.0; https://www.tensorflow.org/)
Collate: 'package.R' 'overloaded.R' 'node_class.R' 'node_types.R'
Imports: R6, tensorflow, reticulate, progress, coda
Suggests: knitr, rmarkdown, DiagrammeR, bayesplot, lattice, testthat,
mvtnorm, MCMCpack, rmutil, extraDistr, truncdist