is.dsmm_fit_nonparametric

Checks for the validity of the specified attributes and the
 inheritance of the S3 class <code>dsmm_fit_nonparametric</code>.
 This class inherits methods from the parent class <code>dsmm</code>.

Performs parametric and non-parametric estimation and simulation of
drifting semi-Markov processes. The definition of parametric and non-parametric
model specifications is also possible. Furthermore, three different types of
drifting semi-Markov models are considered. These models differ in the number
of transition matrices and sojourn time distributions used for the computation
of a number of semi-Markov kernels, which in turn characterize the drifting
semi-Markov kernel. For the parametric model estimation and specification,
several discrete distributions are considered for the sojourn times: Uniform,
Poisson, Geometric, Discrete Weibull and Negative Binomial. The non-parametric
model specification makes no assumptions about the shape of the sojourn time
distributions. Semi-Markov models are described in:
Barbu, V.S., Limnios, N. (2008) <doi:10.1007/978-0-387-73173-5>.
Drifting Markov models are described in:
Vergne, N. (2008) <doi:10.2202/1544-6115.1326>.
Reliability indicators of Drifting Markov models are described in:
Barbu, V. S., Vergne, N. (2019) <doi:10.1007/s11009-018-9682-8>.
We acknowledge the DATALAB Project
<https://lmrs-num.math.cnrs.fr/projet-datalab.html> (financed by the
European Union with the European Regional Development fund (ERDF) and by
the Normandy Region) and the HSMM-INCA Project (financed by the French
Agence Nationale de la Recherche (ANR) under grant ANR-21-CE40-0005).

Ioannis Mavrogiannis

dsmmR

Estimation and Simulation of Drifting Semi-Markov Models

Vlad Stefan Barbu

Nicolas Vergne

is.dsmm_fit_nonparametric function

<dl><dt>obj</dt>
<dd>Arbitrary <code>R</code> object.</dd></dl>

Arguments

Check if an object has a valid dsmm_fit_nonparametric class — is.dsmm_fit_nonparametric

<dl>

<dt>obj</dt>
<dd>Arbitrary <code>R</code> object.</dd>

</dl>

is.dsmm_fit_nonparametric: Check if an object has a valid `dsmm_fit_nonparametric` class

Description

Usage

Value

Arguments

See Also