Markov Processes: Characterization and Convergence.
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ID: 289532
1987
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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.
| Reference Key |
openalex_W2126794261
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|---|---|
| Authors | Andris Abakuks, S. N. Ethier, Thomas G. Kurtz |
| Journal | biometrics |
| Year | 1987 |
| DOI |
10.2307/2531839
|
| URL | |
| Keywords | Keywords not found |
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