Add to ORKGThe mimR package (version 1.1.1) for graphical modelling in R is introduced. We present some facilities of mimR, namely those relating specifying models, editing models, fitting models and doing model search. We also discuss the entities needed for flexible graphical modelling in terms of an object structure. An example about a latent variable model is presented. 1 Introduction and background The mimR package provides facilities for graphical modelling in the statistical pro-gram
The R package BGGM provides tools for making Bayesian inference in Gaussian graphical models
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
This article describes the R package mcglm implemented for fitting multivariate covariance generaliz...
The mimR package for graphical modelling in R is introduced. We present some facilities of mimR, nam...
Graphical models in their modern form have been around since the late 1970s and appear today in many...
Graphical models in their modern form have been around for nearly a quarter of a century. Various c...
A graphical model is a class of statistical models that can be represented by a graph which can be u...
The graphical modeling was performed using the R packages “corpcor” [26] and “qgraph” [27].</p
Graphical modelling is a form of multivariate analysis that uses graphs to represent models. They en...
The mplot package provides an easy to use implementation of model stability and variable inclusion p...
We have developed a package, called , consisting of a number of classes and associated methods to su...
This paper presents the R package gRapHD for efficient selection of high-dimensional undirected grap...
The gRbase package is intended to set the framework for computer packages for data analysis using gr...
In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The mai...
International audienceIn this article, we present FactoMineR an R package dedicated to multivariate ...
The R package BGGM provides tools for making Bayesian inference in Gaussian graphical models
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
This article describes the R package mcglm implemented for fitting multivariate covariance generaliz...
The mimR package for graphical modelling in R is introduced. We present some facilities of mimR, nam...
Graphical models in their modern form have been around since the late 1970s and appear today in many...
Graphical models in their modern form have been around for nearly a quarter of a century. Various c...
A graphical model is a class of statistical models that can be represented by a graph which can be u...
The graphical modeling was performed using the R packages “corpcor” [26] and “qgraph” [27].</p
Graphical modelling is a form of multivariate analysis that uses graphs to represent models. They en...
The mplot package provides an easy to use implementation of model stability and variable inclusion p...
We have developed a package, called , consisting of a number of classes and associated methods to su...
This paper presents the R package gRapHD for efficient selection of high-dimensional undirected grap...
The gRbase package is intended to set the framework for computer packages for data analysis using gr...
In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The mai...
International audienceIn this article, we present FactoMineR an R package dedicated to multivariate ...
The R package BGGM provides tools for making Bayesian inference in Gaussian graphical models
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
This article describes the R package mcglm implemented for fitting multivariate covariance generaliz...