Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Hardcover. Condizione: New. 5th Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press CUP, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Aggiungi al carrelloHardback. Condizione: New. This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Itô's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences.
Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 96,07
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Lingua: Inglese
Editore: Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Aggiungi al carrelloHardback. Condizione: New. This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Itô's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences.
Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 5th edition. 419 pages. 10.00x7.00x1.00 inches. In Stock.
Lingua: Inglese
Editore: Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.
EUR 115,03
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Aggiungi al carrelloHardback. Condizione: New. This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Itô's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences.
Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: preigu, Osnabrück, Germania
EUR 103,10
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Aggiungi al carrelloBuch. Condizione: Neu. Probability | Rick Durrett | Buch | Gebunden | Englisch | 2019 | Cambridge University Press | EAN 9781108473682 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: Cambridge University Press Apr 2019, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 125,27
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Itô's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences.
Lingua: Inglese
Editore: Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: Rarewaves.com UK, London, Regno Unito
EUR 120,37
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Aggiungi al carrelloHardback. Condizione: New. This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Itô's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences.
Lingua: Inglese
Editore: Cambridge University Press Apr 2019, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: Books-by-Floh, Paderborn, Germania
EUR 125,81
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware -This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Itô's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences. 432 pp. Englisch.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Ito's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences. The new edition of this lively but rigorous introduction to measure theoretic probability theory, designed for use in a graduate course, contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), a topic that is finding new applications. Some 200 examples and 450 exercises help readers build practical intuition. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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EUR 98,24
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Aggiungi al carrelloHardcover. Condizione: Brand New. 5th edition. 419 pages. 10.00x7.00x1.00 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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EUR 102,26
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Aggiungi al carrelloHardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: CitiRetail, Stevenage, Regno Unito
EUR 103,81
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Ito's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences. The new edition of this lively but rigorous introduction to measure theoretic probability theory, designed for use in a graduate course, contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), a topic that is finding new applications. Some 200 examples and 450 exercises help readers build practical intuition. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 136,56
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Lingua: Inglese
Editore: Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: moluna, Greven, Germania
EUR 101,47
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The new edition of this lively but rigorous introduction to measure theoretic probability theory, designed for use in a graduate course, contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs).
Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 141,68
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of Ito's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences. The new edition of this lively but rigorous introduction to measure theoretic probability theory, designed for use in a graduate course, contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), a topic that is finding new applications. Some 200 examples and 450 exercises help readers build practical intuition. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.