ggplot2, glasso, huge, fdrtool, d3Network, ggm, gtools,
Description: Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
Packaged: 2018-04-25 08:37:11 UTC; sachaepskamp

person("Giulio", "Costantini", role = c("aut")),
person("Jonas", "Haslbeck", role = c("aut")),
person("Angelique O. J.", "Cramer", role = c("ctb")),
person("Lourens J.", "Waldorp", role = c("ctb")),
person("Verena D.", "Schmittmann", role = c("ctb")),
person("Denny", "Borsboom", role = c("ctb")))
Imports: Rcpp (>= 1.0.0), methods, grDevices, psych, lavaan, plyr,
Hmisc, igraph, jpeg, png, colorspace, Matrix, corpcor,
reshape2, ggplot2, glasso, huge, fdrtool, d3Network, ggm,
gtools, BDgraph, parallel, pbapply, abind
Packaged: 2019-02-13 11:19:08 UTC; sachaepskamp

Packaged: 2019-05-09 09:46:12 UTC; sachaepskamp

person("Adela", "Isvoranu", role = c("aut")),
Packaged: 2019-06-19 12:52:16 UTC; sachaepskamp

gtools, BDgraph, parallel, pbapply, abind, dplyr, tidygraph,

reshape2, ggplot2, glasso, huge, fdrtool, d3Network, gtools,
BDgraph, parallel, pbapply, abind, dplyr, tidygraph, ggraph
Packaged: 2020-02-21 18:18:50 UTC; sachaepskamp

reshape2, ggplot2, glasso, fdrtool, gtools, parallel, pbapply,

Packaged: 2019-01-24 13:26:16 UTC; sachaepskamp

Packaged: 2022-03-04 11:49:30 UTC; sachaepskamp

Title: A 'shiny' Application for Active Learning Instruction in
Description: A 'shiny' application for teaching introductory quantitative genetics
and plant breeding through interactive simulations. The application relies on
established plant breeding and quantitative genetic theory found in
Author: Jeffrey Neyhart [aut, cre] (<https://orcid.org/0000-0002-1991-5310>)

Title: Tools for Quantitative Genetics Data Analyses
Author: Jixiang Wu (South Dakota State University), Johnie N. Jenkins and Jack C. McCarty (USDA-ARS)
Description: Two linear mixed model approaches: REML(restricted maximum likelihood) and MINQUE (minimum norm quadratic unbiased estimation) approaches and several resampling techniques are integrated for various quantitative genetics analyses. With these two types of approaches, various unbalanced data structures, missing data, and any irregular genetic  mating designs can be analyzed and statistically tested. This package also offers fast computations for many large data sets. Other functions will be added to this R tool in the future.