semimetric.pca

Computes a semi-metric based on the first ncomp principal component scores.

Functional data analysis tools with a high-performance 'Rust' backend.
Provides methods for functional data manipulation, depth computation,
distance metrics, regression, and statistical testing. Supports both
1D functional data (curves) and 2D functional data (surfaces).
Methods are described in Ramsay and Silverman (2005,
ISBN:978-0-387-40080-8) "Functional Data Analysis" and Ferraty and
Vieu (2006, ISBN:978-0-387-30369-7) "Nonparametric Functional Data
Analysis".

Dr. Mueller

fdars

Functional Data Analysis in 'Rust'

Simon Müller

semimetric.pca function

<dl><dt>fdataobj</dt>
<dd>An object of class 'fdata'.</dd>
<dt>fdataref</dt>
<dd>An object of class 'fdata'. If NULL, uses fdataobj.</dd>
<dt>ncomp</dt>
<dd>Number of principal components to use.</dd>
<dt>...</dt>
<dd>Additional arguments (ignored).</dd></dl>

Arguments

Semi-metric based on Principal Components — semimetric.pca

<dl>

<dt>fdataobj</dt>
<dd>An object of class 'fdata'.</dd>


<dt>fdataref</dt>
<dd>An object of class 'fdata'. If NULL, uses fdataobj.</dd>


<dt>ncomp</dt>
<dd>Number of principal components to use.</dd>


<dt>...</dt>
<dd>Additional arguments (ignored).</dd>

</dl>

semimetric.pca: Semi-metric based on Principal Components

Description

Usage

Value

Arguments

Examples