pls: msc – R documentation

Pricing

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

Get Started for Free

Documentation

pls

msc

Multiplicative Scatter Correction

Description

Performs multiplicative scatter/signal correction on a data matrix.

Usage

msc(X, reference = NULL)
## S3 method for class 'msc'
predict(object, newdata, ...)
## S3 method for class 'msc'
makepredictcall(var, call)

Arguments

`X, newdata`	numeric matrices. The data to scatter correct.
`reference`	numeric vector. Spectre to use as reference. If `NULL`, the column means of `X` are used.
`object`	an object inheriting from class `"msc"`, normally the result of a call to `msc` with a single matrix argument.
`var`	A variable.
`call`	The term in the formula, as a call.
`...`	other arguments. Currently ignored.

Details

makepredictcall.msc is an internal utility function; it is not meant for interactive use. See makepredictcall for details.

Value

Both msc and predict.msc return a multiplicative scatter corrected matrix, with attribute "reference" the vector used as reference spectre. The matrix is given class c("msc", "matrix"). For predict.msc, the "reference" attribute of object is used as reference spectre.

Author(s)

Bjørn-Helge Mevik and Ron Wehrens

References

Martens, H., Næs, T. (1989) Multivariate calibration. Chichester: Wiley.

Examples

data(yarn)
## Direct correction:
Ztrain <- msc(yarn$NIR[yarn$train,])
Ztest <- predict(Ztrain, yarn$NIR[!yarn$train,])

## Used in formula:
mod <- plsr(density ~ msc(NIR), ncomp = 6, data = yarn[yarn$train,])
pred <- predict(mod, newdata = yarn[!yarn$train,]) # Automatically scatter corrected

pls

Partial Least Squares and Principal Component Regression

v2.7-3

GPL-2

Authors

Bjørn-Helge Mevik [aut, cre], Ron Wehrens [aut], Kristian Hovde Liland [aut], Paul Hiemstra [ctb]

Initial release

2020-08-04

msc