projector

A <code>projector</code> maps a matrix from an N-dimensional space to d-dimensional space, where <code>d</code> may be less than <code>N</code>.
The projection matrix, <code>v</code>, is not necessarily orthogonal. This function constructs a <code>projector</code> instance which can be
used for various dimensionality reduction techniques like PCA, LDA, etc.

Provides a set of basic and extensible data structures and functions for multivariate analysis, including dimensionality reduction techniques, projection methods, and preprocessing functions. The aim of this package is to offer a flexible and user-friendly framework for multivariate analysis that can be easily extended for custom requirements and specific data analysis tasks.

Bradley Buchsbaum

multivarious

Extensible Data Structures for Multivariate Analysis

projector function

<dl><dt>v</dt>
<dd>A matrix of coefficients with dimensions <code>nrow(v)</code> by <code>ncol(v)</code> (columns = components)</dd>
<dt>preproc</dt>
<dd>A prepped pre-processing object (S3 class <code>pre_processor</code>). Default is the no-op <code>pass()</code> preprocessor.</dd>
<dt>...</dt>
<dd>Extra arguments to be stored in the <code>projector</code> object.</dd>
<dt>classes</dt>
<dd>Additional class information used for creating subtypes of <code>projector</code>. Default is NULL.</dd></dl>

Arguments

Construct a projector instance — projector

<dl>

<dt>v</dt>
<dd>A matrix of coefficients with dimensions <code>nrow(v)</code> by <code>ncol(v)</code> (columns = components)</dd>


<dt>preproc</dt>
<dd>A prepped pre-processing object (S3 class <code>pre_processor</code>). Default is the no-op <code>pass()</code> preprocessor.</dd>


<dt>...</dt>
<dd>Extra arguments to be stored in the <code>projector</code> object.</dd>


<dt>classes</dt>
<dd>Additional class information used for creating subtypes of <code>projector</code>. Default is NULL.</dd>

</dl>

projector: Construct a `projector` instance

Description

Usage

Value

Arguments