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A User's Guide to Measure Theoretic Probability (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 8) - Hardcover
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...
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...
About the Author
David Pollard is Reader in Strategy and Business Analysis at Leeds Metropolitan University.
"About this title" may belong to another edition of this title.
- PublisherCambridge University Press
- Publication date2001
- ISBN 10 0521802423
- ISBN 13 9780521802420
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages366
- Rating
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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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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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ISBN 13: 9780521802420
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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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ISBN 10: 0521802423
ISBN 13: 9780521802420
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A User's Guide to Measure Theoretic Probability (Hardcover)
Published by
Cambridge University Press, Cambridge, 2001
ISBN 10: 0521802423
ISBN 13: 9780521802420
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Hardcover. Condition: new. Hardcover. Rigorous probabilistic arguments, built on the foundation of measure theory introduced seventy 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 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. This book offers a rigorous probability course. It covers the basic topics of independence, conditioning, martingales, convergence in distribution, and Fourier transforms plus more advanced topics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521802420
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A User's Guide to Measure Theoretic Probability (Hardcover)
Published by
Cambridge University Press, Cambridge, 2001
ISBN 10: 0521802423
ISBN 13: 9780521802420
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Hardcover
First Edition
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Hardcover. Condition: new. Hardcover. Rigorous probabilistic arguments, built on the foundation of measure theory introduced seventy 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 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. This book offers a rigorous probability course. It covers the basic topics of independence, conditioning, martingales, convergence in distribution, and Fourier transforms plus more advanced topics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521802420
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A User's Guide to Measure Theoretic Probability
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ISBN 10: 0521802423
ISBN 13: 9780521802420
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