predict_opls

Predicts response values based on a model generated by either by <code>opls</code> or the <code>fopls</code> functions.
For internal use only!.

internal

Functions for dissimilarity analysis and memory-based learning
(MBL, a.k.a local modeling) in complex spectral data sets.
Most of these functions are based on the methods presented in
Ramirez-Lopez et al. (2013) <doi:10.1016/j.geoderma.2012.12.014>.

Leonardo RamirezLopez

resemble

Memory-Based Learning in Spectral Chemometrics

predict_opls function

<dl><dt>bo</dt>
<dd>a numeric value indicating the intercept.</dd>
<dt>b</dt>
<dd>the matrix of regression coefficients.</dd>
<dt>ncomp</dt>
<dd>an integer value indicating how may components must be used in the prediction.</dd>
<dt>newdata</dt>
<dd>a matrix containing the predictor variables.</dd>
<dt>scale</dt>
<dd>a logical indicating whether the matrix of predictors used to create the regression model was scaled.</dd>
<dt>Xscale</dt>
<dd>if <code>scale = TRUE</code> a matrix of one row with the values that must be used for scaling <code>newdata</code>.</dd></dl>

Arguments

Author

Prediction function for the opls and fopls functions — predict_opls

<dl>

<dt>bo</dt>
<dd>a numeric value indicating the intercept.</dd>


<dt>b</dt>
<dd>the matrix of regression coefficients.</dd>


<dt>ncomp</dt>
<dd>an integer value indicating how may components must be used in the prediction.</dd>


<dt>newdata</dt>
<dd>a matrix containing the predictor variables.</dd>


<dt>scale</dt>
<dd>a logical indicating whether the matrix of predictors used to create the regression model was scaled.</dd>


<dt>Xscale</dt>
<dd>if <code>scale = TRUE</code> a matrix of one row with the values that must be used for scaling <code>newdata</code>.</dd>

</dl>

predict_opls: Prediction function for the `opls` and `fopls` functions

Description

Usage

Value

Arguments

Author