Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Añadir al carritoHardcover. Condición: New. 5th Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Añadir al carritoHardcover. Condición: 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press CUP, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Añadir al carritoHardback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Idioma: Inglés
Publicado por Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Añadir al carritoHardback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
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Añadir al carritoHardcover. Condición: Brand New. 5th edition. 419 pages. 10.00x7.00x1.00 inches. In Stock.
Idioma: Inglés
Publicado por Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 115,05
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Añadir al carritoHardback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: preigu, Osnabrück, Alemania
EUR 103,10
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Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press Apr 2019, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, GB, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: Rarewaves.com UK, London, Reino Unido
EUR 120,40
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Añadir al carritoHardback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press Apr 2019, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: Books-by-Floh, Paderborn, Alemania
EUR 125,81
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: 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.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 98,26
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Añadir al carritoHardcover. Condición: Brand New. 5th edition. 419 pages. 10.00x7.00x1.00 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 102,28
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Añadir al carritoHardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: CitiRetail, Stevenage, Reino Unido
EUR 103,84
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Añadir al carritoHardcover. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 136,56
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Añadir al carritoCondición: New. PRINT ON DEMAND.
Idioma: Inglés
Publicado por Cambridge University Press, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: moluna, Greven, Alemania
EUR 101,47
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Añadir al carritoGebunden. Condición: 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).
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2019
ISBN 10: 1108473687 ISBN 13: 9781108473682
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 141,70
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Añadir al carritoHardcover. Condición: 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.