A generic function to extract the ID attribute from an object.

Tools for fitting and simulating mixtures of Watson distributions.
The package is described in Sablica, Hornik and Leydold (2026) <doi:10.18637/jss.v115.i04>.
The random sampling scheme of the package offers two sampling
algorithms that are based of the results of Sablica, Hornik and Leydold (2022)
<doi:10.1080/10618600.2024.2416521>.
What is more, the package offers a smart tool to combine these two methods,
and based on the selected parameters, it approximates the relative sampling
speed for both methods and picks the faster one. In addition, the package
offers a fitting function for the mixtures of Watson distribution, that
uses the expectation-maximization (EM) algorithm. Special features are
the possibility to use multiple variants of the E-step and M-step,
sparse matrices for the data representation and state of the art methods
for numerical evaluation of needed special functions using the results of
Sablica and Hornik (2022) <doi:10.1090/mcom/3690> and
Sablica and Hornik (2024) <doi:10.1016/j.jmaa.2024.128262>.

Lukas Sablica

watson

Fitting and Simulating Mixtures of Watson Distributions

Kurt Hornik

Josef Leydold

Gerard Jungman

Brian Gough

id function

<dl><dt>object</dt>
<dd>An object from which to extract the ID attribute.</dd>
<dt>...</dt>
<dd>Additional arguments.</dd></dl>

Arguments

Generic Function for Extracting IDs — id

<dl>

<dt>object</dt>
<dd>An object from which to extract the ID attribute.</dd>


<dt>...</dt>
<dd>Additional arguments.</dd>

</dl>

id: Generic Function for Extracting IDs

Description

Usage

Value

Arguments