cellulose: NIR-Viscosity example data set to illustrate multivariate...

In SamGG/ropls: PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data

Description

The data were collected at Akzo Nobel, Ornkoldsvik (Sweden). The raw material for their cellulose derivative process is delivered to the factory in form of cellulose sheets. Before entering the process the cellulose sheets are controlled by a viscosity measurement, which functions as a steering parameter for that particular batch. In this data set NIR spectra for 180 cellulose sheets were collected after the sheets had been sent through a grinding process. Hence the NIR spectra were measured on the cellulose raw material in powder form. Data are divided in two parts, one used for modeling and one part for testing.

Format

A list with the following elements:

• nirMN a matrix of 180 samples x 1201 wavelengths in the VIS-NIR region

• viscoVn a vector (length = 180) of viscosity of cellulose powder

• classVn a vector (length = 180) of class membership (1 or 2)

Value

For details see the Format section above.

References

Multivariate calibration using spectral data. Simca tutorial. Umetrics.

SamGG/ropls documentation built on May 29, 2019, 1:51 a.m.