bimfdplot

Bivariate plot for `mvmfd` objects

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

bimfdplot function

<dl><dt>mvmfd_obj</dt>
<dd>An `mvmfd` object</dd>
<dt>type</dt>
<dd>Type of plot ('l' for lines, 'p' for points, etc.)</dd>
<dt>lty</dt>
<dd>Line type</dd>
<dt>xlab</dt>
<dd>Label for the x-axis</dd>
<dt>ylab</dt>
<dd>Label for the y-axis</dd>
<dt>main</dt>
<dd>Main title</dd>
<dt>...</dt>
<dd>Additional arguments for the matplot function</dd></dl>

Arguments

Bivariate plot for `mvmfd` objects — bimfdplot

<dl>

<dt>mvmfd_obj</dt>
<dd>An `mvmfd` object</dd>


<dt>type</dt>
<dd>Type of plot ('l' for lines, 'p' for points, etc.)</dd>


<dt>lty</dt>
<dd>Line type</dd>


<dt>xlab</dt>
<dd>Label for the x-axis</dd>


<dt>ylab</dt>
<dd>Label for the y-axis</dd>


<dt>main</dt>
<dd>Main title</dd>


<dt>...</dt>
<dd>Additional arguments for the matplot function</dd>

</dl>

bimfdplot: Bivariate plot for `mvmfd` objects

Description

Usage

Arguments

See Also