Package: dsmmR 1.0.6
dsmmR: Estimation and Simulation of Drifting Semi-Markov Models
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).
Authors:
dsmmR_1.0.6.tar.gz
dsmmR_1.0.6.zip(r-4.5)dsmmR_1.0.6.zip(r-4.4)dsmmR_1.0.6.zip(r-4.3)
dsmmR_1.0.6.tgz(r-4.4-any)dsmmR_1.0.6.tgz(r-4.3-any)
dsmmR_1.0.6.tar.gz(r-4.5-noble)dsmmR_1.0.6.tar.gz(r-4.4-noble)
dsmmR_1.0.6.tgz(r-4.4-emscripten)dsmmR_1.0.6.tgz(r-4.3-emscripten)
dsmmR.pdf |dsmmR.html✨
dsmmR/json (API)
NEWS
| # Install 'dsmmR' in R: |
| install.packages('dsmmR', repos = c('https://mavrogiannis-ioannis.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mavrogiannis-ioannis/dsmmr/issues
- lambda - Lambda genome
Last updated 1 months agofrom:13ec4afcb3. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 06 2024 |
| R-4.5-win | OK | Sep 06 2024 |
| R-4.5-linux | OK | Sep 06 2024 |
| R-4.4-win | OK | Sep 06 2024 |
| R-4.4-mac | OK | Sep 06 2024 |
| R-4.3-win | OK | Sep 06 2024 |
| R-4.3-mac | OK | Sep 06 2024 |
Exports:create_sequencefit_dsmmget_kernelis.dsmmis.dsmm_fit_nonparametricis.dsmm_fit_parametricis.dsmm_nonparametricis.dsmm_parametricnonparametric_dsmmparametric_dsmm
Dependencies:DiscreteWeibullRsolnptruncnorm
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| dsmmR : Estimation and Simulation of Drifting Semi-Markov Models | dsmmR-package dsmmR |
| Simulate a sequence for states of choice. | create_sequence |
| Estimation of a drifting semi-Markov chain | dsmm_fit fit_dsmm |
| Obtain the Drifting semi-Markov kernel | get_kernel |
| Check if an object has a valid 'dsmm' class | is.dsmm |
| Check if an object has a valid 'dsmm_fit_nonparametric' class | is.dsmm_fit_nonparametric |
| Check if an object has a valid 'dsmm_fit_parametric' class | is.dsmm_fit_parametric |
| Check if an object has a valid 'dsmm_nonparametric' class | is.dsmm_nonparametric |
| Check if an object has a valid 'dsmm_parametric' class | is.dsmm_parametric |
| lambda genome | lambda |
| Non-parametric Drifting semi-Markov model specification | dsmm_nonparametric nonparametric nonparametric_dsmm |
| Parametric Drifting semi-Markov model specification | dsmm_parametric parametric parametric_dsmm |
| Simulate a sequence given a drifting semi-Markov kernel. | dsmm_simulate simulate.dsmm |
