Imports: methods, parallel, crochet (>= 2.1.0), bigmemory,
Suggests: data.table (>= 1.9.6), lme4, SKAT, testthat, covr
Packaged: 2018-08-24 20:04:31 UTC; amphysvena

Packaged: 2019-01-25 19:14:58 UTC; agrueneberg

Suggests: data.table (>= 1.9.6), lme4, SKAT, testthat
Packaged: 2020-08-02 13:06:47 UTC; agrueneberg

Packaged: 2021-10-04 13:54:48 UTC; agrueneberg

Packaged: 2021-12-08 14:16:25 UTC; agrueneberg

Title: Bayesian Genomic Linear Models Applied to GE Genome Selection
Authors@R: c(person("Italo", "Granato", email = "italo.granato@gmail.com", role = c("aut", "cre")),
person("Luna-Vázquez", "Francisco J.", email = "frahik@gmail.com ", role =c("aut")),
person("Cuevas", "Jaime", email = "jaicueva@uqroo.edu.mx", role =c("aut")))
Description: Application of genome prediction for a continuous variable, focused
on genotype by environment (GE) genomic selection models (GS). It consists a group of functions
that help to create regression kernels for some GE genomic models proposed by Jarquín et al. (2014) <doi:10.1007/s00122-013-2243-1>
and Lopez-Cruz et al. (2015) <doi:10.1534/g3.114.016097>. Also, it computes genomic predictions based on Bayesian approaches.
The prediction function uses an orthogonal transformation of the data and specific priors
Packaged: 2017-11-30 18:23:27 UTC; Italo Granato

Packaged: 2018-05-10 16:38:29 UTC; Italo Granato

Packaged: 2018-05-15 22:03:05 UTC; Italo Granato

Packaged: 2018-07-23 18:46:09 UTC; Italo Granato

Packaged: 2018-08-10 14:54:06 UTC; Italo Granato

Title: Bayesian Gaussian Graphical Models
Authors@R: c(person("Donald", "Williams", email = "drwwilliams@ucdavis.edu", role = c("aut", "cre")),
person("Joris", "Mulder", email = "J.Mulder3@uvt.nl", role = "aut"))
Description: Fit Bayesian Gaussian graphical models. The methods are separated into
two Bayesian approaches for inference: hypothesis testing and estimation. There are
extensions for confirmatory hypothesis testing, comparing Gaussian graphical models,
and node wise predictability. These methods were recently introduced in the Gaussian
Williams and Mulder (2019) <doi:10.31234/osf.io/ypxd8>,
Williams, Rast, Pericchi, and Mulder (2019) <doi:10.31234/osf.io/yt386>.
Imports: mvnfast (>= 0.2.5), foreach (>= 1.4.7), doParallel (>=