Isbn: 9780521002899 - a user's guide to measure theoretic probability (cambridge series in statistical and probabilistic mathematics, 8) (7 Ergebnisse)

Paperback. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Zustand: New. In English.

Zustand: New. This 2002 book is a secure starting point for anyone who needs to invoke rigorous probabilistic arguments and understand what they mean. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 366 pages, 200 exercises. BIC Classification: PBT. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 253 x 179 x 21. Weight in Grams: 662. . 2002. paperback. . . . . Books ship from the US and Ireland. …

Zustand: New.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Rigorous probabilistic arguments, built on the foundation of measure theory introduced eighty years ago by Kolmogorov, have invaded many fields. Students of statistics, biostatistics, econometrics, finance, and other changing disciplines now find themselves needing to absorb theory beyond what they might have learned in the typical undergraduate, calculus-based probability course. This 2002 book grew from a one-semester course offered for many years to a mixed audience of graduate and undergraduate students who have not had the luxury of taking a course in measure theory. The core of the book covers the basic topics of independence, conditioning, martingales, convergence in distribution, and Fourier transforms. In addition there are numerous sections treating topics traditionally thought of as more advanced, such as coupling and the KMT strong approximation, option pricing via the equivalent martingale measure, and the isoperimetric inequality for Gaussian processes. The book is not just a presentation of mathematical theory, but is also a discussion of why that theory takes its current form. It will be a secure starting point for anyone who needs to invoke rigorous probabilistic arguments and understand what they mean.…