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Denumerable Markov Chains - neues Buch
2012, ISBN: 9781468494556
with a chapter of Markov Random Fields by David Griffeath, eBooks, eBook Download (PDF), [PU: Springer New York], Springer New York, 2012
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Denumerable Markov Chains : with a chapter of Markov Random Fields by David Griffeath - neues Buch
ISBN: 9781468494556
With the first edition out of print, we decided to arrange for republi- cation of Denumerrible Markov Ohains with additional bibliographic material.The new edition contains a section Addi… Mehr…
John G. Kemeny; Anthony W. Knapp; J. Laurie Snell:
Denumerable Markov Chains - neues Buch2012, ISBN: 9781468494556
with a chapter of Markov Random Fields by David Griffeath, eBooks, eBook Download (PDF), With the first edition out of print, we decided to arrange for republi- cation of Denumerrible Mar… Mehr…
Denumerable Markov Chains - neues Buch
ISBN: 9781468494556
With the first edition out of print, we decided to arrange for republi cation of Denumerrible Markov Ohains with additional bibliographic material. The new edition contains a section Ad… Mehr…
Denumerable Markov Chains - neues Buch
ISBN: 9781468494556
Denumerable Markov Chains - with a chapter of Markov Random Fields by David Griffeath: ab 69.49 € eBooks > Fachthemen & Wissenschaft > Mathematik Springer New York eBook als pdf, Springer… Mehr…
Denumerable Markov Chains - neues Buch
2012, ISBN: 9781468494556
with a chapter of Markov Random Fields by David Griffeath, eBooks, eBook Download (PDF), [PU: Springer New York], Springer New York, 2012
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Detailangaben zum Buch - Denumerable Markov Chains
EAN (ISBN-13): 9781468494556
Erscheinungsjahr: 2012
Herausgeber: Springer New York
Buch in der Datenbank seit 2016-08-04T03:21:45+02:00 (Berlin)
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ISBN/EAN: 9781468494556
ISBN - alternative Schreibweisen:
978-1-4684-9455-6
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: kemeny snell, anthony knapp, john snell, han baltussen
Titel des Buches: denumerable markov chains
Daten vom Verlag:
Autor/in: John G. Kemeny; J. Laurie Snell; Anthony W. Knapp
Titel: Graduate Texts in Mathematics; Denumerable Markov Chains - with a chapter of Markov Random Fields by David Griffeath
Verlag: Springer; Springer US
484 Seiten
Erscheinungsjahr: 2012-12-06
New York; NY; US
Sprache: Englisch
69,54 € (DE)
71,50 € (AT)
77,00 CHF (CH)
Available
XII, 484 p.
EA; E107; eBook; Nonbooks, PBS / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Brownian motion; Chains; Markov; Markov chain; Markov property; Martingale; Random Walk; Random variable; Stochastic processes; measure theory; stochastic process; C; Probability Theory and Stochastic Processes; Analysis; Probability Theory; Analysis; Mathematics and Statistics; Stochastik; Mathematische Analysis, allgemein; BB
1: Prerequisites from Analysis.- 1. Denumerable Matrices.- 2. Measure Theory.- 3. Measurable Functions and Lebesgue Integration.- 4. Integration Theorems.- 5. Limit Theorems for Matrices.- 6. Some General Theorems from Analysis.- 2: Stochastic Processes.- 1. Sequence Spaces.- 2. Denumerable Stochastic Processes.- 3. Borel Fields in Stochastic Processes.- 4. Statements of Probability Zero or One.- 5. Conditional Probabilities.- 6. Random Variables and Means.- 7. Means Conditional on Statements.- 8. Problems.- 3: Martingales.- 1. Means Conditional on Partitions and Functions.- 2. Properties of Martingales.- 3. A First Martingale Systems Theorem.- 4. Martingale Convergence and a Second Systems Theorem.- 5. Examples of Convergent Martingales.- 6. Law of Large Numbers.- 7. Problems.- 4: Properties of Markov Chains.- 1. Markov Chains.- 2. Examples of Markov Chains.- 3. Applications of Martingale Ideas.- 4. Strong Markov Property.- 5. Systems Theorems for Markov Chains.- 6. Applications of Systems Theorems.- 7. Classification of States.- 8. Problems.- 5: Transient Chains.- 1. Properties of Transient Chains.- 2. Superregular Functions.- 3. Absorbing Chains.- 4. Finite Drunkard’s Walk.- 5. Infinite Drunkard’s Walk.- 6. A Zero-One Law for Sums of Independent Random Variables.- 7. Sums of Independent Random Variables on the Line.- 8. Examples of Sums of Independent Random Variables.- 9. Ladder Process for Sums of Independent Random Variables.- 10. The Basic Example.- 11. Problems.- 6: Recurrent Chains.- 1. Mean Ergodic Theorem for Markov Chains.- 2. Duality.- 3. Cyclicity.- 4. Sums of Independent Random Variables.- 5. Convergence Theorem for Noncyclic Chains.- 6. Mean First Passage Time Matrix.- 7. Examples of the Mean First Passage Time Matrix.- 8. Reverse Markov Chains.- 9. Problems.- 7: Introduction to Potential Theory.- 1. Brownian Motion.- 2. Potential Theory.- 3. Equivalence of Brownian Motion and Potential Theory.- 4. Brownian Motion and Potential Theory in n Dimensions.- 5. Potential Theory for Denumerable Markov Chains.- 6. Brownian Motion as a Limit of the Symmetric Random Walk.- 7. Symmetric Random Walk in n Dimensions.- 8: Transient Potential Theory.- 1. Potentials.- 2. The h-Process and Some Applications.- 3. Equilibrium Sets and Capacities.- 4. Potential Principles.- 5. Energy.- 6. The Basic Example.- 7. An Unbounded Potential.- 8. Applications of Potential-Theoretic Methods.- 9. General Denumerable Stochastic Processes.- 10. Problems.- 9: Recurrent Potential Theory.- 1. Potentials.- 2. Normal Chains.- 3. Ergodic Chains.- 4. Classes of Ergodic Chains.- 5. Strong Ergodic Chains.- 6. The Basic Example.- 7. Further Examples.- 8. The Operator K.- 9. Potential Principles.- 10. A Model for Potential Theory.- 11. A Nonnormal Chain and Other Examples.- 12. Two-Dimensional Symmetric Random Walk.- 13. Problems.- 10: Transient Boundary Theory.- 1. Motivation for Martin Boundary Theory.- 2. Extended Chains.- 3. Martin Exit Boundary.- 4. Convergence to the Boundary.- 5. Poisson-Martin Representation Theorem.- 6. Extreme Points of the Boundary.- 7. Uniqueness of the Representation.- 8. Analog of Fatou’s Theorem.- 9. Fine Boundary Functions.- 10. Martin Entrance Boundary.- 11. Application to Extended Chains.- 12. Proof of Theorem 10.9.- 13. Examples.- 14. Problems.- 11: Recurrent Boundary Theory.- 1. Entrance Boundary for Recurrent Chains.- 2. Measures on the Entrance Boundary.- 3. Harmonic Measure for Normal Chains.- 4. Continuous and T-Continuous Functions.- 5. Normal Chains and Convergence to the Boundary.- 6. Representation Theorem.- 7. Sums of Independent Random Variables.- 8. Examples.- 9. Problems.- 12: Introduction to Random Fields.- 1 Markov Fields.- 2. Finite Gibbs Fields.- 3. Equivalence of Finite Markov and Neighbor Gibbs Fields.- 4. Markov Fields and Neighbor Gibbs Fields: the Infinite Case.- 5. Homogeneous Markov Fields on the Integers.- 6. Examples of Phase Multiplicity in Higher Dimensions.- 7. Problems.- Notes.- Additional Notes.- References.- Additional References.- Index of Notation.This textbook provides a systematic treatment of denumerable Markov chains, covering both the foundations of the subject and some in topics in potential theory and boundary theory. The book is a careful exposition with special emphasis on the clarity of style and presentation.
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