This function is used by <code>mds.ct</code> to fit a symmetric version of 
the sandwich smoother of Xiao et al. (2013).

Implements a basis function or functional data analysis framework
for several techniques of multivariate analysis in continuous-time
setting. Specifically, we introduced continuous-time analogues of
several classical techniques of multivariate analysis, such as
principal component analysis, canonical correlation analysis,
Fisher linear discriminant analysis, K-means clustering, and so
on. Details are in Biplab Paul, Philip T. Reiss, Erjia Cui and Noemi Foa (2025)
"Continuous-time multivariate analysis" <doi: 10.1080/10618600.2024.2374570>.

Biplab Paul

ctmva

Continuous-Time Multivariate Analysis

Philip Tzvi Reiss

Noemi Foa

Dror Arbiv

s3 function

<dl><dt>Y</dt>
<dd>a square symmetric matrix</dd>
<dt>B</dt>
<dd>a B-spline basis evaluation matrix</dd>
<dt>P</dt>
<dd>a penalty matrix</dd>
<dt>lambda</dt>
<dd>a vector of smoothing parameter values</dd></dl>

Arguments

Philip Tzvi Reiss &lt;reiss@stat.haifa.ac.il&gt;

Author

Symmetric sandwich smoother — s3

<dl>

<dt>Y</dt>
<dd>a square symmetric matrix</dd>


<dt>B</dt>
<dd>a B-spline basis evaluation matrix</dd>


<dt>P</dt>
<dd>a penalty matrix</dd>


<dt>lambda</dt>
<dd>a vector of smoothing parameter values</dd>

</dl>

s3: Symmetric sandwich smoother

Description

Usage

Value

Arguments

Author

References

See Also

Examples