PeakPurity {ImpuR}R Documentation

Perform peak purity analysis

Description

Calculate a bilinear model and estimate noise from a spectime object and perform window evolving factor analysis.

Usage

PeakPurity(object, hetero = NULL, wefa.margin = 10, bilinear.model = "svd", err.win = 1:20, svd.nsvd = 4, peel.specfirst = FALSE, peel.direction = rep(c("left", "right"), 2), favor.positive = FALSE, verbose = FALSE)

Arguments

object a spectime object
hetero whether to do heteroscedasticity correction in wefa
wefa.margin window width for wefa
bilinear.model which bilinear model to use (svd or peel)
err.win times (rows) on which to estimage noise
svd.nsvd number of singular components in svd
peel.specfirst peeling: whether to peel spectrum first
peel.direction peeling: come from "left" (top) or "right" (bottom)
favor.positive whether to favor positive components
verbose echo stages

Details

Use ErrorComponents to calculate noise. Then use Globalsvd or Peel to extract bilinear model. The carry out window evolving factor analysis.

Value

a spectime object for which the slots @std.err, @hetero, @ct, @spec, @WEAtime, @WEAwavelength are filled in.

Author(s)

Christian Ritter

References

Ritter C. and Gilliard J. (2007), JSS

Examples

data(al1)
plot(PeakPurity(al1,bilinear.model="svd"))
plot(PeakPurity(al1,bilinear.model="peel"))

[Package ImpuR version 1.0 Index]