kernels

<p>Parametric covariance functions (kernels) used to define the covariance
structure of Gaussian processes. These can be used with <code>make_gaussian_process</code>
to generate synthetic functional data.</p>

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

kernels: Covariance Kernel Functions for Gaussian Processes

Description

Arguments

Value