get_wapls_weights

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

Leonardo Ramirez-Lopez

Antoine Stevens

Claudio Orellano

Raphael Viscarra Rossel

Alex Wadoux

get_wapls_weights function

<dl><dt>pls_model</dt>
<dd>either an object returned by the <code>pls_cv</code> function or an
object as returned by the <code>opls_get_basics</code> function which contains a pls model.</dd>
<dt>original_x</dt>
<dd>the original spectral matrix which was used for calibrating the
pls model.</dd>
<dt>type</dt>
<dd>type of weight to be computed. The only available option (for
the moment) is <code>"w1"</code>. See details on the <code>mbl</code> function where it
is explained how <code>"w1"</code> is computed whitin the <code>"wapls"</code>
regression.</dd>
<dt>new_x</dt>
<dd>a vector of a new spectral observation. When "w1" is selected, new_x
must be specified.</dd>
<dt>pls_c</dt>
<dd>a vector of length 2 which contains both the minimum and maximum
number of PLS components for which the weights must be computed.</dd></dl>

Arguments

Leonardo Ramirez-Lopez and Antoine Stevens

Author

Internal function for computing the weights of the PLS components
necessary for weighted average PLS — get_wapls_weights

<dl>

<dt>pls_model</dt>
<dd>either an object returned by the <code>pls_cv</code> function or an
object as returned by the <code>opls_get_basics</code> function which contains a pls model.</dd>


<dt>original_x</dt>
<dd>the original spectral matrix which was used for calibrating the
pls model.</dd>


<dt>type</dt>
<dd>type of weight to be computed. The only available option (for
the moment) is <code>"w1"</code>. See details on the <code>mbl</code> function where it
is explained how <code>"w1"</code> is computed whitin the <code>"wapls"</code>
regression.</dd>


<dt>new_x</dt>
<dd>a vector of a new spectral observation. When "w1" is selected, new_x
must be specified.</dd>


<dt>pls_c</dt>
<dd>a vector of length 2 which contains both the minimum and maximum
number of PLS components for which the weights must be computed.</dd>

</dl>

get_wapls_weights: Internal function for computing the weights of the PLS components necessary for weighted average PLS

Description

Usage

Value

Arguments

Author