getNumFlag

This function checks whether the columns in a data frame (or a vector) are of
type numeric, integer, or logical. It can return a logical vector indicating
whether each column matches these types, or, if <code>index = TRUE</code>, it returns
the indices of the matching columns.

A novel forward stepwise discriminant analysis framework
that integrates Pillai's trace with Uncorrelated Linear Discriminant Analysis (ULDA),
providing an improvement over traditional stepwise LDA methods that rely on Wilks' Lambda.
A stand-alone ULDA implementation is also provided, offering a more general solution
than the one available in the 'MASS' package. It automatically handles missing values and
provides visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2409.03136>.

Siyu Wang

folda

Forward Stepwise Discriminant Analysis with Pillai's Trace

getNumFlag function

<dl><dt>data</dt>
<dd>A data frame or a vector. The function will check the data types
of the columns (if <code>data</code> is a data frame) or the type of the vector.</dd>
<dt>index</dt>
<dd>A logical value. If <code>FALSE</code> (default), the function returns a
logical vector indicating which columns are numeric, integer, or logical.
If <code>TRUE</code>, it returns the indices of these columns.</dd></dl>

Arguments

Identify Numeric, Integer, or Logical Columns in a Data Frame — getNumFlag

<dl>

<dt>data</dt>
<dd>A data frame or a vector. The function will check the data types
of the columns (if <code>data</code> is a data frame) or the type of the vector.</dd>


<dt>index</dt>
<dd>A logical value. If <code>FALSE</code> (default), the function returns a
logical vector indicating which columns are numeric, integer, or logical.
If <code>TRUE</code>, it returns the indices of these columns.</dd>

</dl>

getNumFlag: Identify Numeric, Integer, or Logical Columns in a Data Frame

Description

Usage

Value

Arguments