Standard deviation an object of class `mfd`.

Methods and tools for implementing regularized multivariate functional principal component analysis ('ReMFPCA') for multivariate functional data whose variables might be observed over different dimensional domains. 'ReMFPCA' is an object-oriented interface leveraging the extensibility and scalability of R6. It employs a parameter vector to control the smoothness of each functional variable. By incorporating smoothness constraints as penalty terms within a regularized optimization framework, 'ReMFPCA' generates smooth multivariate functional principal components, offering a concise and interpretable representation of the data. For detailed information on the methods and techniques used in 'ReMFPCA', please refer to Haghbin et al. (2023) <doi:10.48550/arXiv.2306.13980>.

Hossein Haghbin

ReMFPCA

Regularized Multivariate Functional Principal Component Analysis

Yue Zhao

Mehdi Maadooliat

sd function

<dl><dt>x</dt>
<dd>An object of class `mfd`</dd>
<dt>...</dt>
<dd>all `sd` function arguments.</dd></dl>

Arguments

Standard deviation of an object of class `mfd`. — sd

<dl>

<dt>x</dt>
<dd>An object of class `mfd`</dd>


<dt>...</dt>
<dd>all `sd` function arguments.</dd>

</dl>

sd: Standard deviation of an object of class `mfd`.

Description

Usage

Value

Arguments