CNV.fitModel: Fits a mixture of Gaussian to a set of one dimensional...
In CNVtools: A package to test genetic association with CNV data

Description Usage Arguments Details Value Author(s) See Also

This is the workhorse function, essentially an R wrapper around a lot of C code. It fits GLM models to the data.

CNV.fitModel(ncomp, 
	     nind, 
	     hyp = "H0", 
	     data, 
	     logit.offset,
             design.matrix.mean, 
	     design.matrix.variance,
             design.matrix.disease, 
	     pi.model = 0, 
	     mix.model = 10,
             control = list(tol = 1e-05, max.iter = 3000, min.freq= 4))

`ncomp`	integer, number of components to fit to the data
`nind`	integer, total number of data points
`hyp`	Hypothesis, can be either H0 or H1
`data`	The data frame containing the data, in an expanded form (one point per individual and copy number)
`logit.offset`	An option most users will not use. It sets an offset when fitting the logit model for the disease status. This is used to obtain a profile likelihood when the disease parameter beta varies.
`design.matrix.mean`	The design matrix that relate mean cluster locations with batch.copy numbers.
`design.matrix.variance`	The design matrix for the cluster variances.
`design.matrix.disease`	The design matrix for the disease model.
`pi.model`	0,1,2 fit disease, hetero and quantitative models respectively.
`mix.model`	Specifies model for the components.
`control`	A list of parameters that control the behavior of the fitting.

The user is very unlikely to actually use that function which is meant as an internal routine, a wrapper around the C code of the package. This function is called by the more user friendly function CNVtest.binary.