Algorithm 972: JMarkov: An integrated framework for Markov chain modeling
Markov chains (MC) are a powerful tool for modeling complex stochastic systems. Whereas a number of tools exist for solving different types ofMCmodels, the first step inMCmodeling is to define themodel parameters. This step is, however, error prone and far from trivial when modeling complex systems....
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/23121
- Acceso en línea:
- https://doi.org/10.1145/3009968
https://repository.urosario.edu.co/handle/10336/23121
- Palabra clave:
- Chains
Queueing theory
Stochastic models
Stochastic systems
Exponential distributions
Infinite state space
Integrated frameworks
Markov Decision Processes
Optimal decision-rule
Phase type distributions
Quasi-birth and death process
Steady state and transients
Markov processes
Markov chains
Markov decision processes
Phase-type distributions
Quasi-birth-and-death processes
Stochastic modeling
- Rights
- License
- Abierto (Texto Completo)