Vor Ort
Merkzettel Warenkorb
Produktbild: Markov Chains and Invariant Probabilities
Band 211

Markov Chains and Invariant Probabilities

Aus der Reihe Progress in Mathematics

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.10.2012

Verlag

Springer Basel

Seitenzahl

208

Maße (L/B/H)

23,5/15,5/1,3 cm

Gewicht

374 g

Auflage

Softcover reprint of the original 1st ed. 2003

Sprache

Englisch

ISBN

978-3-0348-9408-1

Beschreibung

Rezension

"It should be stressed that an important part of the results presented is due to the authors. . . . In the reviewer's opinion, this is an elegant and most welcome addition to the rich literature of Markov processes."


--MathSciNet

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.10.2012

Verlag

Springer Basel

Seitenzahl

208

Maße (L/B/H)

23,5/15,5/1,3 cm

Gewicht

374 g

Auflage

Softcover reprint of the original 1st ed. 2003

Sprache

Englisch

ISBN

978-3-0348-9408-1

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: GPSR Kontakt

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Markov Chains and Invariant Probabilities
  • 1 Preliminaries.- 1.1 Introduction.- 1.2 Measures and Functions.- 1.3 Weak Topologies.- 1.4 Convergence of Measures.- 1.5 Complements.- 1.6 Notes.- I Markov Chains and Ergodicity.- 2 Markov Chains and Ergodic Theorems.- 2.1 Introduction.- 2.2 Basic Notation and Definitions.- 2.3 Ergodic Theorems.- 2.4 The Ergodicity Property.- 2.5 Pathwise Results.- 2.6 Notes.- 3 Countable Markov Chains.- 3.1 Introduction.- 3.2 Classification of States and Class Properties.- 3.3 Limit Theorems.- 3.4 Notes.- 4 Harris Markov Chains.- 4.1 Introduction.- 4.2 Basic Definitions and Properties.- 4.3 Characterization of Harris recurrence.- 4.4 Sufficient Conditions for P.H.R.- 4.5 Harris and Doeblin Decompositions.- 4.6 Notes.- 5 Markov Chains in Metric Spaces.- 5.1 Introduction.- 5.2 The Limit in Ergodic Theorems.- 5.3 Yosida’s Ergodic Decomposition.- 5.4 Pathwise Results.- 5.5 Proofs.- 5.6 Notes.- 6 Classification of Markov Chains via Occupation Measures.- 6.1 Introduction.- 6.2 A Classification.- 6.3 On the Birkhoff Individual Ergodic Theorem.- 6.4 Notes.- II Further Ergodicity Properties.- 7 Feller Markov Chains.- 7.1 Introduction.- 7.2 Weak-and Strong-Feller Markov Chains.- 7.3 Quasi Feller Chains.- 7.4 Notes.- 8 The Poisson Equation.- 8.1 Introduction.- 8.2 The Poisson Equation.- 8.3 Canonical Pairs.- 8.4 The Cesàro-Averages Approach.- 8.5 The Abelian Approach.- 8.6 Notes.- 9 Strong and Uniform Ergodicity.- 9.1 Introduction.- 9.2 Strong and Uniform Ergodicity.- 9.3 Weak and Weak Uniform Ergodicity.- 9.4 Notes.- III Existence and Approximation of Invariant Probability Measures.- 10 Existence of Invariant Probability Measures.- 10.1 Introduction and Statement of the Problems.- 10.2 Notation and Definitions.- 10.3 Existence Results.- 10.4 Markov Chains in Locally Compact Separable Metric Spaces.- 10.5 Other Existence Results in Locally Compact Separable Metric Spaces.- 10.6 Technical Preliminaries.- 10.7 Proofs.- 10.8 Notes.- 11 Existence and Uniqueness of Fixed Points for Markov Operators.- 11.1 Introduction and Statement of the Problems.- 11.2 Notation and Definitions.- 11.3 Existence Results.- 11.4 Proofs.- 11.5 Notes.- 12 Approximation Procedures for Invariant Probability Measures.- 12.1 Introduction.- 12.2 Statement of the Problem and Preliminaries.- 12.3 An Approximation Scheme.- 12.4 A Moment Approach for a Special Class of Markov Chains.- 12.5 Notes.