Structured Dependence between Stochastic Processes
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1. Introduction; Part I. Consistencies: 2. Strong Markov consistency of multivariate Markov families and processes; 3. Consistency of finite multivariate Markov chains; 4. Consistency of finite multivariate conditional Markov chains; 5. Consistency of multivariate special semimartingales; Part II. Structures: 6. Strong Markov family structures; 7. Markov chain structures; 8. Conditional Markov chain structures; 9. Special semimartingale structures Part III. Further Developments: 10. Archimedean survival processes, Markov consistency, ASP structures; 11. Generalized multivariate Hawkes processes; Part IV. Applications of Stochastic Structures: 12. Applications of stochastic structures; Appendix A. Stochastic analysis: selected concepts and results used in this book; Appendix B. Markov processes and Markov families; Appendix C. Finite Markov chains: auxiliary technical framework; Appendix D. Crash course on conditional Markov chains and on doubly stochastic Markov chains; Appendix E. Evolution systems and semigroups of linear operators; Appendix F. Martingale problem: some new results needed in this book; Appendix G. Function spaces and pseudo-differential operators; References; Notation index; Subject index.
Comprehensive presentation of the technical aspects and applications of the theory of structured dependence between random processes.