lin.cor

This function computed the linear correlation between two vectors or a correlation matrix for an input matrix.
The following methods to compute linear correlations are implemented in this function:

Computes 46 optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.

Hajk-Georg Drost

philentropy

Similarity and Distance Quantification Between Probability
Functions

Jakub Nowosad

lin.cor function

<dl><dt>x</dt>
<dd>a numeric <code>vector</code>, <code>matrix</code>, or <code>data.frame</code>.</dd>
<dt>y</dt>
<dd>a numeric <code>vector</code> that should be correlated with <code>x</code>.</dd>
<dt>method</dt>
<dd>the method to compute the linear correlation between <code>x</code> and <code>y</code>.</dd>
<dt>test.na</dt>
<dd>a boolean value indicating whether input data should be checked for <code>NA</code> values.</dd></dl>

Arguments

Author

Linear Correlation — lin.cor

<dl>

<dt>x</dt>
<dd>a numeric <code>vector</code>, <code>matrix</code>, or <code>data.frame</code>.</dd>


<dt>y</dt>
<dd>a numeric <code>vector</code> that should be correlated with <code>x</code>.</dd>


<dt>method</dt>
<dd>the method to compute the linear correlation between <code>x</code> and <code>y</code>.</dd>


<dt>test.na</dt>
<dd>a boolean value indicating whether input data should be checked for <code>NA</code> values.</dd>

</dl>

lin.cor: Linear Correlation

Description

Usage

Arguments

Author

Details