snv: Standard normal variate transformation (SNV)

In mlesnoff/rnirs: Dimension reduction, Regression and Discrimination for Chemometrics

Standard normal variate transformation (SNV)

Description

SNV transformation of the row observations (usually spectra) of a data set. By default, each observation is centered on its mean and divided by its standard deviation.

Usage

snv(X, center = TRUE, scale = TRUE)

Arguments

X	A matrix or data frame. The column names of X must be integers (usually the wavelengths).
center	Logical. If TRUE (default), the centering in the SNV is done.
scale	Logical. If TRUE (default), the scaling in the SNV is done.

Value

A matrix of the transformed data.

Examples

data(datcass)

X <- datcass$Xu

z <- snv(X)
#z <- snv(X, center = FALSE)

headm(X)
headm(z)

oldpar <- par(mfrow = c(1, 1))
par(mfrow = c(1, 2))
plotsp(X, main = "Signal")
plotsp(z, zeroes = TRUE, main = "Corrected signal")
par(oldpar)

mlesnoff/rnirs documentation built on April 24, 2023, 4:17 a.m.