normalizePrincipalCurve.matrix: Normalizes data in K dimensions using principal curves

In HenrikBengtsson/aroma.cn: Copy-Number Analysis of Large Microarray Data Sets

Normalizes data in K dimensions using principal curves

Description

Normalizes data in K dimensions using principal curves such that afterward the data cluster (approximately linearly) along the diagonal (in K dimensions).

Usage

## S3 method for class 'matrix'
normalizePrincipalCurve(x, ..., center=TRUE, returnFit=FALSE)

Arguments

x	An NxK matrix where the columns represent the (K >= 2) dimensions.
...	Additional arguments passed to fitPrincipalCurve used for fitting the model.
center	If TRUE, normalized data is centered such that the median signal in each dimension is at zero.
returnFit	If TRUE, the fitted principal curve parameters are returned as an attribute.

Value

Returns an NxK matrix.

Author(s)

Henrik Bengtsson

References

[1] Hastie, T. and Stuetzle, W, Principal Curves, JASA, 1989.

See Also

fitPrincipalCurve and backtransformPrincipalCurve.

HenrikBengtsson/aroma.cn documentation built on Feb. 20, 2024, 9:15 p.m.