Type: Package
Package: dsmmR
Title: Estimation and Simulation of Drifting Semi-Markov Models
Version: 1.0.1
Date: 2023-02-03
Authors@R: c(
    person("Vlad Stefan", "Barbu",
           role = c("aut"),
           comment = c(ORCID = "0000-0002-0840-016X")),
    person("Ioannis", "Mavrogiannis", 
        role = c("aut", "cre"),
        email = "mavrogiannis.ioa@gmail.com"),
    person("Nicolas", "Vergne",
           role = c("aut"))
           ) 
Description: 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>.
License: GPL
Imports: DiscreteWeibull
Suggests: utils, knitr, rmarkdown
Encoding: UTF-8
RoxygenNote: 7.2.3
NeedsCompilation: yes
Author: Vlad Stefan Barbu [aut] (<https://orcid.org/0000-0002-0840-016X>),
  Ioannis Mavrogiannis [aut, cre],
  Nicolas Vergne [aut]
Maintainer: Ioannis Mavrogiannis <mavrogiannis.ioa@gmail.com>
Depends: R (>= 2.10)
Packaged: 2023-02-04 19:51:48 UTC; ioann
Repository: CRAN
Date/Publication: 2023-02-04 20:12:31 UTC
