Coupling and Ergodic Theorems for Semi-Markov-Type Processes I Markov Chains, Renewal, and Regenerative Processes /
Ergodic theorems are a cornerstone of the theory of stochastic processes and their applications. This volume delves into ergodic theorems with explicit power and exponential upper bounds for convergence rates, focusing on Markov chains, renewal processes, and regenerative processes. The book offers...
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| Natura: | Elettronico eBook |
| Lingua: | inglese |
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Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edizione: | 1st ed. 2025. |
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| Accesso online: | https://doi.org/10.1007/978-3-031-89311-7 |
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Sommario:
- Preface
- Introduction
- Coupling for Random Variables
- Coupling and Ergodic Theorems for Finite Markov Chains
- Coupling and Ergodic Theorems for General Markov Chains
- Hitting Times and Method of Test Functions
- Approaching of Renewal Schemes
- Synchronizing of Shifted Renewal Schemes
- Coupling for Renewal Schemes
- Coupling and Ergodic Theorems for Regenerative Processes
- Uniform Ergodic Theorems for Regenerative Processes
- Generalized Ergodic Theorems for Regenerative Processes
- Coupling and the Renewal Theorem
- Appendix A. Basic Ergodic Theorems for Regenerative Processes
- Appendix B. Methodological and Bibliographical Notes
- References
- Index.