mixture.plot.JointUniquePairs: Plot the correlation densities of the empirical fit, mixture...
In IdMappingAnalysis: ID Mapping Analysis

Description Usage Arguments Value Author(s) See Also Examples

Plot the correlation densities of the empirical fit, mixture fit and each of the mixture components for a mixture object derived from UniquePairsMatch and Corr objects with optional subsetting by a group of ID Maps. This is achived by first creating a mixture model from the JointUniquePairs and Corr objects with optional subsetting by a group of ID Maps encapsulated within the and then calling the MixtureObject.plot() on a resulting Mixture object.

1 2	## S3 method for class 'JointUniquePairs' mixture.plot(this, corr, idMapNames=NULL, subsetting=FALSE, G=c(1:5), verbose=FALSE, ...)

`corr`	Corr object.
`idMapNames`	If not `NULL`, defines the subset of ID Maps from JointUniquePairs on which the full event group is to be formed. Default is `NULL`.
`subsetting`	If `TRUE`, uses Corr subset to compute the mixture model or uses the original Corr otherwise. Default is `FALSE`.
`G`	The number of mixture model components. If a `numeric` vector, the optimal mixture model is computed. Default is c(1:5).
`verbose`	If `TRUE` enables diagnostic messages. Default is `FALSE`.
`...`	Additional graphical parameters

The Mixture object plotted

Alex Lisovich, Roger Day

For more information see JointUniquePairs.

 #plot the results of mixture fit for a given DB subset and a Corr object (corr.spearman)
 mixtureSet<-examples$jointUniquePairs$mixture.plot(examples$corr,
                idMapNames=c("NetAffx_Q","DAVID_Q","EnVision_Q"),
	          subsetting=TRUE,G=c(1:5),verbose=TRUE);