sample_loo

for internal use only! If group is provided, the
sampling is done based on the groups.

internal

Provides tools to build quantitative chemometric models and
applications for near-infrared (NIR) sensors. Chemometric regression
models are based on partial least squares regression as described by
Wold (1975) <doi:10.1016/B978-0-12-103950-9.50017-4> and modified
partial least squares regression as described by Shenk and Westerhaus
(1991) <doi:10.2135/cropsci1991.0011183X003100020049x>, with further
discussion by Westerhaus (2014) <doi:10.1255/nirn.1492>.

Leonardo Ramirez-Lopez

proximetricsR

Spectral Preprocessing and Chemometric Calibration of NIR
Sensors

Claudio Orellano

Nicolae Cudlenco

Mai Said

Mohamed Abushosha

Marcal Plans

sample_loo function

<dl><dt>N</dt>
<dd>the total number of observations.</dd>
<dt>group</dt>
<dd>the labels for each sample in <code>y</code> indicating the group each
observation belongs to.</dd></dl>

Arguments

A function to create calibration and validation sample sets for
leave-one-out cross-validation — sample_loo

<dl>

<dt>N</dt>
<dd>the total number of observations.</dd>


<dt>group</dt>
<dd>the labels for each sample in <code>y</code> indicating the group each
observation belongs to.</dd>

</dl>

sample_loo: A function to create calibration and validation sample sets for leave-one-out cross-validation

Description

Usage

Value

Arguments