predict_gaussian_process

Predicts response values based on a model generated by the <code>gaussian_process</code> function (Gaussian process regression with dot product covariance). 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_gaussian_process function

<dl><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
(in the <code>gaussian_process</code> function) was scaled</dd>
<dt>Xcenter</dt>
<dd>if <code>center = TRUE</code> a matrix of one row with the values that must be used for centering <code>newdata</code>.</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>
<dt>Ycenter</dt>
<dd>if <code>center = TRUE</code> a matrix of one row with the values that must be used for accounting for the centering of the response variable.</dd>
<dt>Yscale</dt>
<dd>if <code>scale = TRUE</code> a matrix of one row with the values that must be used for accounting for the scaling of the response variable.</dd></dl>

Arguments

Author

Prediction function for the gaussian_process function (Gaussian process regression with dot product covariance) — predict_gaussian_process

<dl>

<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
(in the <code>gaussian_process</code> function) was scaled</dd>


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


<dt>Ycenter</dt>
<dd>if <code>center = TRUE</code> a matrix of one row with the values that must be used for accounting for the centering of the response variable.</dd>


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

</dl>

predict_gaussian_process: Prediction function for the `gaussian_process` function (Gaussian process regression with dot product covariance)

Description

Usage

Value

Arguments

Author