
A Basic Course in Measure and Probability
Theory for Applications
Cambridge University Press
Published on 30. January 2014
Book
Paperback/Softback
374 pages
978-1-107-65252-1 (ISBN)
Description
Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
College/higher education
Product notice
Paperback (trade)
Illustrations
Worked examples or Exercises; 15 Line drawings, unspecified
Dimensions
Height: 226 mm
Width: 150 mm
Thickness: 18 mm
Weight
590 gr
ISBN-13
978-1-107-65252-1 (9781107652521)
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.
Schweitzer Classification
Other editions
Additional editions

Ross Leadbetter | Stamatis Cambanis | Vladas Pipiras
A Basic Course in Measure and Probability
Theory for Applications
E-Book
03/2014
1st Edition
Cambridge University Press
€44.49
Available for download

Ross Leadbetter | Stamatis Cambanis | Vladas Pipiras
A Basic Course in Measure and Probability
Theory for Applications
Book
01/2014
Cambridge University Press
€167.00
Shipment within 15-20 days
Persons
Ross Leadbetter is Professor of Statistics and Operations Research at the University of North Carolina, Chapel Hill. His research involves stochastic process theory and applications, point processes, and particularly extreme value and risk theory for stationary sequences and processes. Stamatis Cambanis was a Professor at the University of North Carolina, Chapel Hill until his death in 1995. He taught a wide range of statistics and probability courses and contributed very significantly to the development of the measure and probability instruction and the lecture notes on which this volume is based. Vladas Pipiras has been with the University of North Carolina, Chapel Hill since 2002 and rose to full Professor in 2012. His main research interests focus on stochastic processes exhibiting long-range dependence, multifractality and other scaling phenomena, as well as on stable, extreme-value and other distributions possessing heavy tails. He has also worked on statistical inference questions for reduced-rank models with applications to econometrics, and sampling issues for finite point processes with applications to data traffic modeling in computer networks.
Author
University of North Carolina, Chapel Hill
University of North Carolina, Chapel Hill
University of North Carolina, Chapel Hill
Content
Preface; Acknowledgements; 1. Point sets and certain classes of sets; 2. Measures: general properties and extension; 3. Measurable functions and transformations; 4. The integral; 5. Absolute continuity and related topics; 6. Convergence of measurable functions, Lp-spaces; 7. Product spaces; 8. Integrating complex functions, Fourier theory and related topics; 9. Foundations of probability; 10. Independence; 11. Convergence and related topics; 12. Characteristic functions and central limit theorems; 13. Conditioning; 14. Martingales; 15. Basic structure of stochastic processes; References; Index.