stand

<code>stand</code> center and scale a data matrix

Classification method obtained through linear programming.
It is advantageous with respect to the classical developments when the distribution of the variables
involved is unknown or when the number of variables is much greater than the number of individuals.
Mathematical details behind the method are published in Nueda, et al. (2022) "LPDA: A new classification method based on linear programming".
<doi:10.1371/journal.pone.0270403>.

Maria Jose Nueda

lpda

Linear Programming Discriminant Analysis

stand function

<dl><dt>X</dt>
<dd>a data matrix with individuals in rows and variables in columns</dd></dl>

Arguments

stand center and scale a data matrix — stand

<dl>

<dt>X</dt>
<dd>a data matrix with individuals in rows and variables in columns</dd>

</dl>

stand: stand center and scale a data matrix

Description

Usage

Value

Arguments