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008			150903s2008 xxu| o |||| 0|eng d
020			_a9780387749785 _99780387749785
024	7		_a10.1007/9780387749785 _2doi
035			_avtls000332560
039		9	_a201509030231 _bVLOAD _c201404122201 _dVLOAD _c201404091931 _dVLOAD _y201402041032 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aKosorok, Michael R. _eautor _9303802
245	1	0	_aIntroduction to Empirical Processes and Semiparametric Inference / _cby Michael R. Kosorok.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aSpringer Series in Statistics, _x0172-7397
500			_aSpringer eBooks
505	0		_aOverview -- An Overview of Empirical Processes -- Overview of Semiparametric Inference -- Case Studies I -- Empirical Processes -- to Empirical Processes -- Preliminaries for Empirical Processes -- Stochastic Convergence -- Empirical Process Methods -- Entropy Calculations -- Bootstrapping Empirical Processes -- Additional Empirical Process Results -- The Functional Delta Method -- Z-Estimators -- M-Estimators -- Case Studies II -- Semiparametric Inference -- to Semiparametric Inference -- Preliminaries for Semiparametric Inference -- Semiparametric Models and Efficiency -- Efficient Inference for Finite-Dimensional Parameters -- Efficient Inference for Infinite-Dimensional Parameters -- Semiparametric M-Estimation -- Case Studies III.
520			_aThis book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. The targeted audience includes statisticians, biostatisticians, and other researchers with a background in mathematical statistics who have an interest in learning about and doing research in empirical processes and semiparametric inference but who would like to have a friendly and gradual introduction to the area. The book can be used either as a research reference or as a textbook. The level of the book is suitable for a second year graduate course in statistics or biostatistics, provided the students have had a year of graduate level mathematical statistics and a semester of probability. The book consists of three parts. The first part is a concise overview of all of the main concepts covered in the book with a minimum of technicalities. The second and third parts cover the two respective main topics of empirical processes and semiparametric inference in depth. The connections between these two topics is also demonstrated and emphasized throughout the text. Each part has a final chapter with several case studies that use concrete examples to illustrate the concepts developed so far. The last two parts also each include a chapter which covers the needed mathematical preliminaries. Each main idea is introduced with a non-technical motivation, and examples are given throughout to illustrate important concepts. Homework problems are also included at the end of each chapter to help the reader gain additional insights. Michael R. Kosorok is Professor and Chair, Department of Biostatistics, and Professor, Department of Statistics and Operations Research, at the University of North Carolina at Chapel Hill. His research has focused on the application of empirical processes and semiparametric inference to statistics and biostatistics. He is a Fellow of both the American Statistical Association and the Institute of Mathematical Statistics. He is an Associate Editor of the Annals of Statistics, Electronic Journal of Statistics, International Journal of Biostatistics, Statistics and Probability Letters, and Statistics Surveys.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387749778
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-74978-5 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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