000			02935nam a22004098i 4500
001			CR9780511806957
003			UkCbUP
005			20200124160223.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101021s2010||||enk o ||1 0|eng|d
020			_a9780511806957 (ebook)
020			_z9780521877220 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA276 _b.S358 2010
082	0	0	_a519.5 _222
100	1		_aSen, Pranab Kumar, _d1937- _eauthor.
245	1	0	_aFrom finite sample to asymptotic methods in statistics / _cPranab K. Sen, Julio M. Singer, Antonio C. Pedroso de Lima.
264		1	_aCambridge : _bCambridge University Press, _c2010.
300			_a1 online resource (xii, 386 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aCambridge series on statistical and probabilistic mathematics ; _v29
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aMotivation and basic tools -- Estimation theory -- Hypothesis testing -- Elements of statistical decision theory -- Stochastic processes: an overview -- Stochastic convergence and probability inequalities -- Asymptotic distributions -- Asymptotic behavior of estimators and tests -- Categorical data models -- Regression models -- Weak convergence and Gaussian processes.
520			_aExact statistical inference may be employed in diverse fields of science and technology. As problems become more complex and sample sizes become larger, mathematical and computational difficulties can arise that require the use of approximate statistical methods. Such methods are justified by asymptotic arguments but are still based on the concepts and principles that underlie exact statistical inference. With this in perspective, this book presents a broad view of exact statistical inference and the development of asymptotic statistical inference, providing a justification for the use of asymptotic methods for large samples. Methodological results are developed on a concrete and yet rigorous mathematical level and are applied to a variety of problems that include categorical data, regression, and survival analyses. This book is designed as a textbook for advanced undergraduate or beginning graduate students in statistics, biostatistics, or applied statistics but may also be used as a reference for academic researchers.
650		0	_aMathematical statistics.
650		0	_aProbabilities.
650		0	_aEstimation theory.
650		0	_aAsymptotic expansions.
700	1		_aSinger, Julio da Motta, _d1950- _eauthor.
700	1		_aLima, Antonio C. Pedroso de, _d1961- _eauthor.
776	0	8	_iPrint version: _z9780521877220
830		0	_aCambridge series on statistical and probabilistic mathematics ; _v29.
856	4	0	_uhttps://doi.org/10.1017/CBO9780511806957
999			_c516942 _d516940