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Introduction to Statistical Limit Theory
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Introduction to Statistical Limit Theory

Book Details

Format Hardback or Cased Book
ISBN-10 1420076604
ISBN-13 9781420076608
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Jan 7th, 2011
Print length 646 Pages
Weight 1,060 grams
Dimensions 24.10 x 16.40 x 3.80 cms
Product Classification: Probability & statistics
Ksh 27,900.00
Werezi Extended Catalogue 0 in stock

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Reviews approximation theory and limit theory for sequences of functions and basic notions of functional analysis. This title provides arguments that show how underlying mathematical and statistical theory work together. It covers expansion theory and discusses bootstrap, kernel smoothing, and Markov chain Monte Carlo.

Helping students develop a good understanding of asymptotic theory, Introduction to Statistical Limit Theory provides a thorough yet accessible treatment of common modes of convergence and their related tools used in statistics. It also discusses how the results can be applied to several common areas in the field.





The author explains as much of the background material as possible and offers a comprehensive account of the modes of convergence of random variables, distributions, and moments, establishing a firm foundation for the applications that appear later in the book. The text includes detailed proofs that follow a logical progression of the central inferences of each result. It also presents in-depth explanations of the results and identifies important tools and techniques. Through numerous illustrative examples, the book shows how asymptotic theory offers deep insight into statistical problems, such as confidence intervals, hypothesis tests, and estimation.





With an array of exercises and experiments in each chapter, this classroom-tested book gives students the mathematical foundation needed to understand asymptotic theory. It covers the necessary introductory material as well as modern statistical applications, exploring how the underlying mathematical and statistical theories work together.


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