Pork

The spectrum curves of Raman spectroscopy and the percentages of the unsaturated fatty
 acid obtained from 105 samples of the fat taken from the daily
 production stock of a slaughterhouse.

datasets

Signal compression methods for functional regression. It includes various function-on-function (FOF) regression models such as the linear FOF model with functional response and both scalar and functional predictors for a small number of functional predictors, linear FOF models with a large number of functional predictors, linear FOF model for spiky data, stepwise selection for FOF models with two-way interactions, and nonlinear FOF models. It also includes scalar-on-function regression models with single (SOF) or multivariate (mSOF) scalar response variable, and SOF model for spiky data.

Ruiyan Luo

FRegSigCom

Functional Regression using Signal Compression Approach

Pork function

A list of two matrix:<dl class="dl-horizontal">
 <dt>X</dt><dd>a matrix with 105 rows and 566 columns with each row
 representing the spectrum curve of Raman spectroscopy from one fat sample.</dd>
 <dt>Y</dt><dd>a vector of length 105, giving the percentages of the
 unsaturated fatty acid of the 105 samples.</dd>
 </dl>

Format

Pork fat samples — Pork

A list of two matrix:<dl class='dl-horizontal'>
 <dt>X</dt><dd>a matrix with 105 rows and 566 columns with each row
 representing the spectrum curve of Raman spectroscopy from one fat sample.</dd>
 <dt>Y</dt><dd>a vector of length 105, giving the percentages of the
 unsaturated fatty acid of the 105 samples.</dd>
 </dl>

Pork: Pork fat samples

Description

Usage

Arguments

Format

References

See Also

Examples