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A User's Guide to Measure Theoretic Probability - Softcover
Book 8 of 64: Cambridge Series in Statistical and Probabilistic Mathematics
Synopsis
This 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.
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Book Description
Rigorous probabilistic arguments, built on the foundation of measure theory introduced seventy years ago by Kolmogorov, have invaded many fields. Many 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 book grew from a one-semester course offered for many years to a mixed audience of graduate and undergraduate students, who were expected only to have taken an undergraduate course in real analysis or advanced calculus.
About the Author
David Pollard is Reader in Strategy and Business Analysis at Leeds Metropolitan University.
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A User's Guide to Measure Theoretic Probability (Cambridge Series in Statistical and Probabilistic Mathematics)
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Cambridge University Press, 2001
ISBN 10: 0521002893
ISBN 13: 9780521002899
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A User's Guide to Measure Theoretic Probability
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A User's Guide to Measure Theoretic Probability
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A User's Guide to Measure Theoretic Probability (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 8)
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A User's Guide to Measure Theoretic Probability
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A User's Guide to Measure Theoretic Probability (Cambridge Series in Statistical and Probabilistic Mathematics)
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ISBN 13: 9780521002899
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Paperback. Condition: New. 1st. 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. Seller Inventory # LU-9780521002899
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