Produktbild: Stationary Processes and Discrete Parameter Markov Processes
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Stationary Processes and Discrete Parameter Markov Processes

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

03.12.2022

Abbildungen

XVII, 449 p. 5 illus.

Verlag

Springer

Seitenzahl

449

Maße (L/B/H)

24,1/16/2,9 cm

Gewicht

948 g

Auflage

1st ed. 2022

Sprache

Englisch

ISBN

978-3-031-00941-9

Beschreibung

Rezension

"The book is an advanced level measure theoretic probability book. ... The book is an impressive presentation of material, including a huge variety of topics in probability. Because of the wealth of subjects, there is an abundance of possible research topics waiting to challenge new (or experienced) probability experts. This book would be an excellent text for an advanced probability course, and is certainly a valuable reference for those interested in the exciting field of probability." (Myron Hlynka, Mathematical Reviews, March, 2025)

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

03.12.2022

Abbildungen

XVII, 449 p. 5 illus.

Verlag

Springer

Seitenzahl

449

Maße (L/B/H)

24,1/16/2,9 cm

Gewicht

948 g

Auflage

1st ed. 2022

Sprache

Englisch

ISBN

978-3-031-00941-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Stationary Processes and Discrete Parameter Markov Processes
  • Symbol Definition List.- 1. Fourier Analysis: A Brief.- 2. Weakly Stationary Processes and their Spectral Measures.- 3. Spectral Representation of Stationary Processes.- 4. Birkhoff’s Ergodic Theorem.- 5. Subadditive Ergodic Theory.- 6. An Introduction to Dynamical Systems.- 7. Markov Chains.- 8. Markov Processes with General State Space.- 9. Stopping Times and the Strong Markov Property.- 10. Transience and Recurrence of Markov Chains.- 11. Birth–Death Chains.- 12. Hitting Probabilities & Absorption.- 13. Law of Large Numbers and Invariant Probability for Markov Chains by Renewal Decomposition.- 14. The Central Limit Theorem for Markov Chains by Renewal Decomposition.- 15. Martingale Central Limit Theorem.- 16. Stationary Ergodic Markov Processes: SLLN & FCLT.- 17. Linear Markov Processes.- 18. Markov Processes Generated by Iterations of I.I.D. Maps.- 19. A Splitting Condition and Geometric Rates of Convergence to Equilibrium.- 20. Irreducibility and Harris Recurrent Markov Processes.- 21. An Extended Perron–Frobenius Theorem and Large Deviation Theory for Markov Processes.- 22. Special Topic: Applications of Large Deviation Theory.- 23. Special Topic: Associated Random Fields, Positive Dependence, FKG Inequalities.- 24. Special Topic: More on Coupling Methods and Applications.- 25. Special Topic: An Introduction to Kalman Filter.- A. Spectral Theorem for Compact Self-Adjoint Operators and Mercer’s Theorem.- B. Spectral Theorem for Bounded Self-Adjoint Operators.- C. Borel Equivalence for Polish Spaces.- D. Hahn–Banach, Separation, and Representation Theorems in Functional Analysis.- References.- Author Index.- Subject Index.