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Markov Processes: Characterization and Convergence.
Biometrics · 1987 · Vol. 43(2) · pp. 484–484
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.
Stochastic processes and statistical mechanicsMarkov chainMathematicsMarkov processApplied mathematicsConvergence (economics)Stochastic processWeak convergenceCharacterization (materials science)Convergence of random variablesStatistical physics
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