Continuous time Markov processes: an introduction
"Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes and applies this theory to various special examples. The initial chapter is devoted to the most important classical example--one-dimensi...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Providence, RI
American Mathemathical Society
2010
|
| Schriftenreihe: | Graduate studies in mathematics
113 |
| Schlagworte: | |
| Online-Zugang: | UBM01 |
| Zusammenfassung: | "Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes and applies this theory to various special examples. The initial chapter is devoted to the most important classical example--one-dimensional Brownian motion. This, together with a chapter on continuous time Markov chains, provides the motivation for the general setup based on semigroups and generators. Chapters on stochastic calculus and probabilistic potential theory give an introduction to some of the key areas of application of Brownian motion and its relatives. A chapter on interacting particle systems treats a more recently developed class of Markov processes that have as their origin problems in physics and biology."--Publisher's description. |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 1 Online-Ressource (XII, 271 Seiten) Diagramme |
| ISBN: | 9781470411756 |
Internformat
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| 490 | 0 | |a Graduate studies in mathematics |v 113 | |
| 500 | |a Includes bibliographical references and index | ||
| 520 | 3 | |a "Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes and applies this theory to various special examples. The initial chapter is devoted to the most important classical example--one-dimensional Brownian motion. This, together with a chapter on continuous time Markov chains, provides the motivation for the general setup based on semigroups and generators. Chapters on stochastic calculus and probabilistic potential theory give an introduction to some of the key areas of application of Brownian motion and its relatives. A chapter on interacting particle systems treats a more recently developed class of Markov processes that have as their origin problems in physics and biology."--Publisher's description. | |
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Datensatz im Suchindex
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| author | Liggett, Thomas M. 1944-2020 |
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| author_sort | Liggett, Thomas M. 1944-2020 |
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| callnumber-first | Q - Science |
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| callnumber-subject | QA - Mathematics |
| classification_rvk | SK 620 SK 820 |
| classification_tum | MAT 607f |
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| ctrlnum | (OCoLC)1024117547 (DE-599)BVBBV045247550 |
| dewey-full | 519.2/33 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.2/33 |
| dewey-search | 519.2/33 |
| dewey-sort | 3519.2 233 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| id | DE-604.BV045247550 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:12:43Z |
| institution | BVB |
| isbn | 9781470411756 |
| language | English |
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| physical | 1 Online-Ressource (XII, 271 Seiten) Diagramme |
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| publishDate | 2010 |
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| publisher | American Mathemathical Society |
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| series2 | Graduate studies in mathematics |
| spelling | Liggett, Thomas M. 1944-2020 Verfasser (DE-588)10877869X aut Continuous time Markov processes an introduction Thomas M. Liggett Providence, RI American Mathemathical Society 2010 1 Online-Ressource (XII, 271 Seiten) Diagramme txt rdacontent c rdamedia cr rdacarrier Graduate studies in mathematics 113 Includes bibliographical references and index "Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes and applies this theory to various special examples. The initial chapter is devoted to the most important classical example--one-dimensional Brownian motion. This, together with a chapter on continuous time Markov chains, provides the motivation for the general setup based on semigroups and generators. Chapters on stochastic calculus and probabilistic potential theory give an introduction to some of the key areas of application of Brownian motion and its relatives. A chapter on interacting particle systems treats a more recently developed class of Markov processes that have as their origin problems in physics and biology."--Publisher's description. Markov processes Stochastic integrals Markov-Prozess (DE-588)4134948-9 gnd rswk-swf Stochastisches Integral (DE-588)4126478-2 gnd rswk-swf Markov-Prozess (DE-588)4134948-9 s Stochastisches Integral (DE-588)4126478-2 s DE-604 Erscheint auch als Druck-Ausgabe 978-0-8218-4949-1 |
| spellingShingle | Liggett, Thomas M. 1944-2020 Continuous time Markov processes an introduction Markov processes Stochastic integrals Markov-Prozess (DE-588)4134948-9 gnd Stochastisches Integral (DE-588)4126478-2 gnd |
| subject_GND | (DE-588)4134948-9 (DE-588)4126478-2 |
| title | Continuous time Markov processes an introduction |
| title_auth | Continuous time Markov processes an introduction |
| title_exact_search | Continuous time Markov processes an introduction |
| title_full | Continuous time Markov processes an introduction Thomas M. Liggett |
| title_fullStr | Continuous time Markov processes an introduction Thomas M. Liggett |
| title_full_unstemmed | Continuous time Markov processes an introduction Thomas M. Liggett |
| title_short | Continuous time Markov processes |
| title_sort | continuous time markov processes an introduction |
| title_sub | an introduction |
| topic | Markov processes Stochastic integrals Markov-Prozess (DE-588)4134948-9 gnd Stochastisches Integral (DE-588)4126478-2 gnd |
| topic_facet | Markov processes Stochastic integrals Markov-Prozess Stochastisches Integral |
| work_keys_str_mv | AT liggettthomasm continuoustimemarkovprocessesanintroduction |