pls (version 1.2-1)

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, \dots)
## 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.

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.

encoding

latin1

Details

makepredictcall.msc is an internal utility function; it is noe meant for interactive use. See makepredictcall for details.

References

Martens, H., N�s, T. (1989) Multivariate calibration. Chichester: Wiley.

See Also

mvr, pcr, plsr, stdize

Examples

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

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