# snv: Standard and Robust Normal Variate transformations In spectacles: Storing, Manipulating and Analysis Spectroscopy and Associated Data

## 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

 ```1 2 3``` ```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

• Barnes, R.J., Dhanoa, M.S., Lister, S.J. 1989. Standard normal variate transformation and detrending of near-infra-red diffuse reflectance spectra. Applied Spectroscopy 43, 772–777.

• Guo, Q., Wu, W., Massar, D.L. 1999. The robust normal variate transform for pattern recognition with near-infrared data. Analytica Chimica Acta 382:1–2, 87–103.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```# 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.