fast_diss

Computes distances between two data matrices using
"euclid", "cor", "cosine"

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

fast_diss function

<dl><dt>X</dt>
<dd>a matrix</dd>
<dt>Y</dt>
<dd>a matrix</dd>
<dt>method</dt>
<dd>a <code>string</code> with possible values "euclid", "cor", "cosine"</dd></dl>

Arguments

Antoine Stevens and Leonardo Ramirez-Lopez

Author

A fast distance algorithm for two matrices written in C++ — fast_diss

<dl>

<dt>X</dt>
<dd>a matrix</dd>


<dt>Y</dt>
<dd>a matrix</dd>


<dt>method</dt>
<dd>a <code>string</code> with possible values "euclid", "cor", "cosine"</dd>

</dl>

fast_diss: A fast distance algorithm for two matrices written in C++

Description

Usage

Value

Arguments

Author