A basic course in measure and probability theory for applications

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 an...

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Bibliographic Details
Main Authors: Leadbetter, M.R, Cambanis, Stamatis (Author), Pipiras, Vladas (Author)
Format: eBook
Language:English
Published: Cambridge Cambridge University Press 2014
Subjects:
Online Access:
Collection: Cambridge Books Online - Collection details see MPG.ReNa
Description
Summary: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
Physical Description:xiv, 360 pages digital
ISBN:9781139103947