snv: Standard and Robust Normal Variate transformations

Description Usage Arguments Value Author(s) References Examples

View source: R/preprocessing.R

Description

Standard and Robust Normal Variate transformations are often used in chemometrics to normalise a spectra collection and remove the baseline effect.

The Standard Normal Variate transformation (SNV, Barnes et al., 1989) is a common method to reduce within-class variance.

The Robust Normal Variate transformation (RNV, Guo et al., 1999) is a modification of the SNV to make it more robust to closure problems.

These function are to be used in conjonction with apply_spectra.

Usage

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snv(x)

rnv(x, r)

Arguments

x

a vector of numeric values

r

the percentile to use in the RNV computation

Value

A vector of numeric values

Author(s)

Pierre Roudier pierre.roudier@gmail.com

References

Examples

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# Loading example data
data(australia)
spectra(australia) <- sr_no ~ ... ~ 350:2500

# Standard Normal Variate transform
s <- apply_spectra(australia[1:10,], snv)
plot(s)

# The scale function in the base package is actually doing
# the same thing!
s <- apply_spectra(australia[1:10,], scale, center = TRUE, scale = TRUE)
plot(s)

# Robust Normal Variate transform
s <- apply_spectra(australia[1:10,], rnv, r = 0.25)
plot(s)

spectacles documentation built on Jan. 13, 2021, 8:46 a.m.