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Markov Processes: Characterization and Convergence.
Abstract
Introduction. 1. Operator Semigroups. 2. Stochastic Processes and Martingales. 3. Convergence of Probability Measures. 4. Generators and Markov Processes. 5. Stochastic Integral Equations. 6. Random Time Changes. 7. Invariance Principles and Diffusion Approximations. 8. Examples of Generators. 9. Branching Processes. 10. Genetic Models. 11. Density Dependent Population Processes. 12. Random Evolutions. Appendixes. References. Index. Flowchart.
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Cited by
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Roberts, G. O., Gelman, A., & Gilks, W. R. (1997) · The Annals of Applied Probability · doi:10.1214/aoap/1034625254 · Cited by 1,693
Entanglement and Non-Markovianity of Quantum Evolutions
Rivas, Á., Huelga, S. F., & Plenio, M. B. (2010) · Physical Review Letters · doi:10.1103/physrevlett.105.050403 · Cited by 1,037
ARCH models as diffusion approximations
Nelson, D. B. (1990) · Journal of Econometrics · doi:10.1016/0304-4076(90)90092-8 · Cited by 938
Open Quantum Systems: An Introduction
Rivas, ´., & Huelga, S. F. (2012) · SpringerBriefs in Physics · doi:10.1007/978-3-642-23354-8 · Cited by 874
General state space Markov chains and MCMC algorithms
Roberts, G. O., & Rosenthal, J. S. (2004) · Probability Surveys · doi:10.1214/154957804100000024 · Cited by 734
Metadata
- Authors
- Abakuks, A., Ethier, S. N., & Kurtz, T. G.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1987-06
- Volume
- 43
- Issue
- 2
- Pages
- 484
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2126794261
- Cited by
- 4,233
- References
- 0
- FWCI
- 34.35
- Type
- journal article
- Language
- en
- Open access
- closed
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