prep_snv: Standard Normal Variate constructor for spectral...

In proximetricsR: Spectral Preprocessing and Chemometric Calibration of NIR Sensors

Standard Normal Variate constructor for spectral preprocessing

Description

\loadmathjax

Creates a preprocessing constructor for applying Standard Normal Variate (SNV) normalisation to spectral data. The constructor is intended to be passed to preprocess_recipe and executed via process.

Usage

prep_snv()

Details

SNV normalises each spectrum row-wise by subtracting its mean and dividing by its standard deviation:

\mjdeqn

SNV_i = \fracx_i - \barx_is_iSNV_i = (x_i - mean(x_i)) / sd(x_i)

where \mjeqnx_ix_i is the signal of the \mjeqniith observation, \mjeqn\barx_i\barx_i is its mean and \mjeqns_is_i its standard deviation. Implemented via standardNormalVariate.

Value

An object of class preprocessing to be used in preprocess_recipe and executed by process.

Author(s)

Leonardo Ramirez-Lopez with code from Antoine Stevens

References

Barnes RJ, Dhanoa MS, Lister SJ. 1989. Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra. Applied spectroscopy, 43(5): 772-777.

See Also

preprocess_recipe, process

Examples

data("proximateCannabis")
X <- proximateCannabis$spc

snv <- prep_snv()
recipe <- preprocess_recipe(snv)
X_snv <- process(X, recipe)

proximetricsR documentation built on Sept. 4, 2026, 5:08 p.m.