standardize.ct

Subtracts the (continuous-time) mean and divides by the (continuous-time) standard
deviation of each of the variables. This is the continuous-time analogue
of taking an \(n \times p\) data matrix, subtracting the mean of each column, and
dividing by the standard deviation of each column, as is done by
<code><a href="/link/scale?package=ctmva&version=1.6.0" data-mini-rdoc="ctmva::scale">scale</a>(..., center=TRUE, scale=TRUE)</code>.

Implements a basis function or functional data analysis framework
for several techniques of multivariate analysis in continuous-time
setting. Specifically, we introduced continuous-time analogues of
several classical techniques of multivariate analysis, such as
principal component analysis, canonical correlation analysis,
Fisher linear discriminant analysis, K-means clustering, and so
on. Details are in Biplab Paul, Philip T. Reiss, Erjia Cui and Noemi Foa (2025)
"Continuous-time multivariate analysis" <doi: 10.1080/10618600.2024.2374570>.

Biplab Paul

ctmva

Continuous-Time Multivariate Analysis

Philip Tzvi Reiss

Noemi Foa

Dror Arbiv

standardize.ct function

<dl><dt>fdobj</dt>
<dd>continuous-time multivariate data set of class <code>"fd"</code></dd></dl>

Arguments

Philip Tzvi Reiss &lt;reiss@stat.haifa.ac.il&gt; and Biplab Paul &lt;paul.biplab497@gmail.com&gt;

Author

Subtracts the (continuous-time) mean and divides by the (continuous-time) standard
deviation of each of the variables. This is the continuous-time analogue
of taking an \(n \times p\) data matrix, subtracting the mean of each column, and
dividing by the standard deviation of each column, as is done by
<code><a href='https://rdrr.io/r/base/scale.html'>scale</a>(..., center=TRUE, scale=TRUE)</code>.

Center and scale a continuous-time multivariate data set — standardize.ct

<dl>

<dt>fdobj</dt>
<dd>continuous-time multivariate data set of class <code>"fd"</code></dd>

</dl>

standardize.ct: Center and scale a continuous-time multivariate data set

Description

Usage

Value

Arguments

Author

See Also