-.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

-.mfd function

<dl><dt>obj1</dt>
<dd>An `mfd` object</dd>
<dt>obj2</dt>
<dd>An `mfd` object or a scalar</dd></dl>

Arguments

Subtract two `mfd` objects — -.mfd

<dl>

<dt>obj1</dt>
<dd>An `mfd` object</dd>


<dt>obj2</dt>
<dd>An `mfd` object or a scalar</dd>

</dl>

-.mfd: Subtract two `mfd` objects

Description

Usage

Value

Arguments

See Also