mixture.plot.JointUniquePairs {IdMappingAnalysis} | R Documentation

## Plot the correlation densities of the empirical fit, mixture fit and each of the mixture components for a mixture object derived from JointUniquePairsand Corr objects

### Description

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.

### Usage

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

### Arguments

`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

### Value

The Mixture object plotted

### Author(s)

Alex Lisovich, Roger Day

### See Also

For more information see `JointUniquePairs`.

### Examples

     #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);

[Package IdMappingAnalysis version 1.28.0 Index]