Description Usage Arguments Value Author(s) References See Also Examples
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".
1 | viz.rmvggm(x,col = c("red", "blue"), net = FALSE, ...)
|
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. |
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. |
Shailesh Tripathi, Frank Emmert-Streib
Margaritis D (2003). Learning Bayesian Network Model Structure from Data. Ph.D. thesis, School of Computer Science, Carnegie-Mellon University, Pittsburgh, PA.
gs, bnlearn
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