summary.mvnorm.c.net: Provides summary of sampeles generated from multivariate...

In mvgraphnorm: Multivariate Gaussian Graphical Model Analysis

Description

Generate boxplot of correlation and inverse correlation matrix of generated sample from the "rmvggm" function. Also plots an inferred network using conditional independence test when "net=TRUE".

Usage

viz.rmvggm(x,col = c("red", "blue"), net = FALSE, ...)

Arguments

x	This is a list object returned by "rmvggm" function.
col	color vector of length 2 for coloring boxplots for edge and non-edge components
net	is a boolean variable if "TRUE" returns a graph object and graph plot. The graph is inferred using conditional independent test using Grow-Shrink (GS) method. For details pleas check "gs" method in "bnlearn" package.
...	check "gs" function inputs in "bnlearn" package.

Value

Returns a list objects chich contains following objects:

covp	plot
covp	'recordplot' object contains the distribution of constrained covariance matrix generated by "HTF", "IPF" or "KIM" algorithm.
covp	'recordplot' object contains the distribution of constrained covariance matrix generated by "HTF", "IPF" or "KIM" algorithm.
covsmp	'recordplot' object contains the distribution of inverse of covariance of sample matrix. The samples are generated from multivariate normal distribution using constrained covariance matrix generated by "HTF", "IPF" or "KIM" algorithm.
netp	'recordplot' object contains networp plot which is inferred from the samples of multivariate normal distribution using constrained covariance matrix generated by "HTF", "IPF" or "KIM" algorithm. The network is inferred using Grow-Shrink (GS) method.
infnet	"igraph" object of inferred network.

Author(s)

Shailesh Tripathi, Frank Emmert-Streib

References

Margaritis D (2003). Learning Bayesian Network Model Structure from Data. Ph.D. thesis, School of Computer Science, Carnegie-Mellon University, Pittsburgh, PA.

See Also

gs, bnlearn

Examples

  a = barabasi.game(20, directed=FALSE)
  ss <- rmvggm(20, net.str=a, 
    method="htf", cor=.4)
  zz <- viz.rmvggm(ss,net=TRUE, 
    undirected=TRUE, test="cor")

  zz$covp
  zz$covsmp
  zz$netp

mvgraphnorm documentation built on May 1, 2019, 9:45 p.m.