GGMselect is a package dedicated to graph estimation in Gaussian Graphical Models. The main functions return the adjacency matrix of an undirected graph estimated from a data matrix.

The Graphical Group Ridge 'GGRidge' package package classifies ridge regression predictors in disjoint groups of conditionally correlated variables and derives different penalties (shrinkage parameters) for these groups of predictors. It combines the ridge regression method with the graphical model for high-dimensional data (i.e. the number of predictors exceeds the number of cases) or ill-conditioned data (e.g. in the presence of multicollinearity among predictors). The package reduces the mean square errors and the extent of over-shrinking of predictors as compared to the ridge method.

c(
person("Jorge N.", "Tendeiro", email = "j.n.tendeiro@rug.nl", role = c("aut","cre")),
person("Sebastian", "Castro-Alvarez", email = "secastroal@gmail.com", role = "aut"))
An implementation of the generalized graded unfolding model (GGUM) in R, see Roberts, Donoghue, and Laughlin (2000) <doi:10.1177/01466216000241001>). It allows to simulate data sets based on the GGUM. It fits the GGUM and the GUM, and it retrieves item and person parameter estimates. Several plotting functions are available (item and test information functions; item and test characteristic curves; item category response curves). Additionally, there are some functions that facilitate the communication between R and 'GGUM2004'. Finally, a model-fit checking utility, MODFIT(), is also available.
stats, utils, psych, abind, viridis, Rdpack, xlsx
Jorge N. Tendeiro [aut, cre],
Sebastian Castro-Alvarez [aut]

c(
person("Jorge N.", "Tendeiro", email = "tendeiro@hiroshima-u.ac.jp", role = c("aut","cre")),
person("Sebastian", "Castro-Alvarez", email = "secastroal@gmail.com", role = "aut"))

Barret Schloerke <bigbear@iastate.edu>, Di Cook
<dicook@iastate.edu>, Heike Hofmann <hofmann@iastate.edu>, and
Hadley Wickham <h.wickham@iastate.edu>
Package contains templates for different plots to be
combined into a plot matrix.