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dsmmR
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Download and install dsmmR package within the R console
Install from CRAN:
install.packages("dsmmR")
Install from Github:
library("remotes")
install_github("cran/dsmmR")
Install by package version:
library("remotes")
install_version("dsmmR", "1.0.5")
Attach the package and use:
library("dsmmR")
Maintained by
Ioannis Mavrogiannis
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-11-16
Latest Update: 2023-09-01
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) .
Drifting Markov models are described in:
Vergne, N. (2008) .
Reliability indicators of Drifting Markov models are described in:
Barbu, V. S., Vergne, N. (2019) .
We acknowledge the DATALAB Project
(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).
How to cite:
Ioannis Mavrogiannis (2022). dsmmR: Estimation and Simulation of Drifting Semi-Markov Models. R package version 1.0.5, https://cran.r-project.org/web/packages/dsmmR. Accessed 22 Dec. 2024.
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Complete documentation for dsmmR
Functions, R codes and Examples using
the dsmmR R package
Some associated functions: create_sequence . dsmmR-package . fit_dsmm . get_kernel . is.dsmm . is.dsmm_fit_nonparametric . is.dsmm_fit_parametric . is.dsmm_nonparametric . is.dsmm_parametric . lambda . nonparametric_dsmm . parametric_dsmm . simulate.dsmm .
Some associated R codes: data.R . dsmmR-package.R . fitmodel.R . generic_functions.R . nonparametric.R . parametric.R . parametric_estimation.R . utils.R . Full dsmmR package functions and examples
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