Multiplicative Scatter Correction

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.
...: other arguments. Currently ignored.
var: A variable.
call: The term in the formula, as a call.

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.

Details

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

References

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

Author

Bjørn-Helge Mevik and Ron Wehrens

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