000			03050cam a22003254a 4500
001			2010045942
003			DLC
005			20151013135848.0
008			101129s2011 flua b 001 0 eng
010			_a 2010045942
020			_a9781420076608 (hardback)
020			_a1420076604 (hardback)
040			_aDLC _cDLC _dYDX _dYDXCP _dCDX _dBWX _dDLC
050	0	0	_aQA273.67 _b.P65 2011
082	0	0	_a519.2 _222
084			_aMAT029000 _2bisacsh
100	1		_aPolansky, Alan M.
245	1	0	_aIntroduction to statistical limit theory / _cAlan M. Polansky.
260			_aBoca Raton, FL : _bChapman & Hall/CRC Press, _cc2011.
300			_axx, 625 p. : _bill. ; _c25 cm.
490	1		_aChapman & Hall/CRC texts in statistical science series
504			_aIncludes bibliographical references and index.
520			_a"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"--Provided by publisher.
520			_a"Those moving on to advanced statistics typically lack the mathematical foundation that allows them to make full use of statistical limit theory. This accessible resource reviews approximation theory and limit theory for sequences of functions and basic notions of functional analysis. It provides detailed arguments that show how underlying mathematical and statistical theory work together. Among its unique qualities, the text covers expansion theory, which is becoming increasingly important in modern applications. It also discusses bootstrap, kernel smoothing, and Markov chain Monte Carlo and includes a wide array of examples and problems from the fundamental to very advanced"--Provided by publisher.
590			_arua 23/04/13
591			_aLoans
650		0	_aLimit theorems (Probability theory)
830		0	_aTexts in statistical science.
942			_2ddc _cBOOK
999			_c831 _d831