rowNorms

a string. Type of normalization to perform. Options are <code>hellinger</code>, <code>ca</code>, <code>z</code>, <code>other</code>

type

optional. A vector to center the columns of X.

center

optional. A vector to scale the values of X.

scale

This function will normalize the rows of a matrix.

A variety of descriptive multivariate analyses with the singular value decomposition,
such as principal components analysis, correspondence analysis, and multidimensional scaling.
See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

Derek Beaton

ExPosition

Exploratory Analysis with the Singular Value Decomposition

rowNorms function

<dl> <dt>X</dt>
<dd>Data matrix</dd> <dt>type</dt>
<dd>a string. Type of normalization to perform. Options are <code>hellinger</code>, <code>ca</code>, <code>z</code>, <code>other</code></dd> <dt>center</dt>
<dd>optional. A vector to center the columns of X.</dd> <dt>scale</dt>
<dd>optional. A vector to scale the values of X.</dd></dl>

Arguments

Author

Normalize the rows of a matrix. — rowNorms

<dl>

 <dt>X</dt>
<dd>Data matrix</dd>

 <dt>type</dt>
<dd>a string. Type of normalization to perform. Options are <code>hellinger</code>, <code>ca</code>, <code>z</code>, <code>other</code></dd>

 <dt>center</dt>
<dd>optional. A vector to center the columns of X.</dd>

 <dt>scale</dt>
<dd>optional. A vector to scale the values of X.</dd>

</dl>

rowNorms: Normalize the rows of a matrix.

Description

Usage

Value

Arguments

Author

Details