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qgraph (version 1.3.5)
Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation
Description
The qgraph package can be used to visualize data as networks as well as provides an interface for visualizing weighted graphical models.
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Install
install.packages('qgraph')
Monthly Downloads
18,929
Version
1.3.5
License
GPL-2
Maintainer
Sacha Epskamp
Last Published
August 31st, 2016
Functions in qgraph (1.3.5)
Search functions
big5groups
Big 5 groups list
findGraph
Search for optimal correlation or partial correlation network
getWmat
Obtain a weights matrix
qgraph.efa
qgraph.efa
qgraph.loadings
qgraph.loadings
makeBW
A qgraph plot can be understood in black and white
print.qgraph
Print edgelist
qgraph.pca
qgraph.pca
qgraph.sem
qgraph: Structural Equation Modelling
plot.qgraph
Plot method for "qgraph"
mat2vec
Weights matrix to vector
qgraph.cfa
CFA using Structural Equation Modelling
qgraph.gui
Graphical user interface for qgraph
qgraph.panel
qgraph.panel
qgraph.animate
Animate a growing network
qgraphMixed
Plots a mixed graph with both directed and undirected edges.
qgraphAnnotate
Annotates a qgraph object with mouseover tooltips in a HTML file
qgraph.semModel
qgraph: SEM model pathdiagram
qgraph.svg
qgraph.svg
qgraph.lavaan
qgraph: Structural Equation Modelling
qgraph.layout.fruchtermanreingold
qgraph.layout.fruchtermanreingold
smallworldIndex
Small-world index of unweighted graph
summary.qgraph
Summary method for "qgraph"
wi2net
Converts precision matrix to partial correlation matrix
VARglm
Computes a vector autoregressive lag-1 model using GLM
big5
Big 5 dataset
averageLayout
Computes an average layout over several graphs
FDRnetwork
Model selection using local False Discovery Rate
centrality
Centrality statistics of graphs
centrality_auto
Automatic centrality statistics of graphs
cor_auto
Automatically compute an apppropriate correlation matrix
as.igraph.qgraph
Converts qgraph object to igraph object.
centrality and clustering plots
Centrality and Clustering plots and tables
EBICglasso
Compute Gaussian graphical model using graphical lasso based on extended BIC criterium.