
Probability with Martingales
David Williams(Autor*in)
Cambridge University Press
Erschienen am 14. Februar 1991
Buch
Hardcover
266 Seiten
978-0-521-40455-6 (ISBN)
Artikel ist vergriffen; siehe Neuauflage
Beschreibung
Probability theory is nowadays applied in a huge variety of fields including physics, engineering, biology, economics and the social sciences. This book is a modern, lively and rigorous account which has Doob's theory of martingales in discrete time as its main theme. It proves important results such as Kolmogorov's Strong Law of Large Numbers and the Three-Series Theorem by martingale techniques, and the Central Limit Theorem via the use of characteristic functions. A distinguishing feature is its determination to keep the probability flowing at a nice tempo. It achieves this by being selective rather than encyclopaedic, presenting only what is essential to understand the fundamentals; and it assumes certain key results from measure theory in the main text. These measure-theoretic results are proved in full in appendices, so that the book is completely self-contained. The book is written for students, not for researchers, and has evolved through several years of class testing. Exercises play a vital role. Interesting and challenging problems, some with hints, consolidate what has already been learnt, and provide motivation to discover more of the subject than can be covered in a single introduction.
Rezensionen / Stimmen
'... one of the best introductions to Martingale theory.' Monatshefte fuer MathematikWeitere Details
Sprache
Englisch
Verlagsort
Cambridge
Großbritannien
Zielgruppe
Für höhere Schule und Studium
Illustrationen
3 Line drawings, unspecified
Maße
Höhe: 235 mm
Breite: 152 mm
Dicke: 20 mm
Gewicht
504 gr
ISBN-13
978-0-521-40455-6 (9780521404556)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Probability with Martingales
Buch
02/1991
Cambridge University Press
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Probability with Martingales
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Cambridge University Press
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Inhalt
1. A branching-process example; Part I. Foundations: 2. Measure spaces; 3. Events; 4. Random variables; 5. Independence; 6. Integration; 7. Expectation; 8. An easy strong law: product measure; Part II. Martingale Theory: 9. Conditional expectation; 10. Martingales; 11. The convergence theorem; 12. Martingales bounded in L2; 13. Uniform integrability; 14. UI martingales; 15. Applications; Part III. Characteristic Functions: 16. Basic properties of CFs; 17. Weak convergence; 18. The central limit theorem; Appendices; Exercises.