S.LLR

Compute the Local Linear Regression (LLR) smoother matrix.
LLR has better boundary bias properties than Nadaraya-Watson.

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

Functional Data Analysis in 'Rust'

Simon Müller

S.LLR function

<dl><dt>tt</dt>
<dd>Evaluation points (numeric vector).</dd>
<dt>h</dt>
<dd>Bandwidth parameter.</dd>
<dt>Ker</dt>
<dd>Kernel function or name. One of "norm", "epa", "tri", "quar",
"cos", "unif".</dd>
<dt>w</dt>
<dd>Optional weights vector of length n.</dd>
<dt>cv</dt>
<dd>Logical. If TRUE, compute leave-one-out cross-validation matrix.</dd></dl>

Arguments

Local Linear Regression Smoother Matrix — S.LLR

<dl>

<dt>tt</dt>
<dd>Evaluation points (numeric vector).</dd>


<dt>h</dt>
<dd>Bandwidth parameter.</dd>


<dt>Ker</dt>
<dd>Kernel function or name. One of "norm", "epa", "tri", "quar",
"cos", "unif".</dd>


<dt>w</dt>
<dd>Optional weights vector of length n.</dd>


<dt>cv</dt>
<dd>Logical. If TRUE, compute leave-one-out cross-validation matrix.</dd>

</dl>

S.LLR: Local Linear Regression Smoother Matrix

Description

Usage

Value

Arguments

Examples