quantsmooth.cv: quantsmooth.cv

In quantsmooth: Quantile smoothing and genomic visualization of array data

Description

Cross validation of smoothing parameters

Usage

  quantsmooth.cv(intensities,smooth.lambda=2, ridge.kappa=0)

Arguments

intensities	numeric vector
smooth.lambda	numeric; see quantsmooth
ridge.kappa	fudge parameter; see quantsmooth

Details

Cross validation is performed by calculating the fit from the even indices on the odd indices and vice versa.

Value

This function returns the sum of squared differences or NA if the fitting function gave an error

Author(s)

Jan Oosting

See Also

getLambdaMin

Examples

	data(chr14)
	# A low value is indicative of a better fit to the data
	quantsmooth.cv(bac.cn[,1],1)
	quantsmooth.cv(bac.cn[,1],2.8)

quantsmooth documentation built on Nov. 8, 2020, 8:27 p.m.