000			03609nam a22003975i 4500
001			298852
003			MX-SnUAN
005			20170705134244.0
007			cr nn 008mamaa
008			150903s2009 gw | o |||| 0|eng d
020			_a9783540856368 _99783540856368
024	7		_a10.1007/9783540856368 _2doi
035			_avtls000352090
039		9	_a201509030933 _bVLOAD _c201405060300 _dVLOAD _y201402171152 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA273.A1-274.9
100	1		_aPeña, Victor H. _eautor _9335461
245	1	0	_aSelf-Normalized Processes : _bLimit Theory and Statistical Applications / _cby Victor H. Peña, Tze Leung Lai, Qi-Man Shao.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2009.
300			_axiii, 275 páginas _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		_aProbability and its Applications, _x1431-7028
500			_aSpringer eBooks
505	0		_aIndependent Random Variables -- Classical Limit Theorems, Inequalities and Other Tools -- Self-Normalized Large Deviations -- Weak Convergence of Self-Normalized Sums -- Stein's Method and Self-Normalized Berry–Esseen Inequality -- Self-Normalized Moderate Deviations and Laws of the Iterated Logarithm -- Cramér-Type Moderate Deviations for Self-Normalized Sums -- Self-Normalized Empirical Processes and U-Statistics -- Martingales and Dependent Random Vectors -- Martingale Inequalities and Related Tools -- A General Framework for Self-Normalization -- Pseudo-Maximization via Method of Mixtures -- Moment and Exponential Inequalities for Self-Normalized Processes -- Laws of the Iterated Logarithm for Self-Normalized Processes -- Multivariate Self-Normalized Processes with Matrix Normalization -- Statistical Applications -- The t-Statistic and Studentized Statistics -- Self-Normalization for Approximate Pivots in Bootstrapping -- Pseudo-Maximization in Likelihood and Bayesian Inference -- Sequential Analysis and Boundary Crossing Probabilities for Self-Normalized Statistics.
520			_aSelf-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is on the front cover. Due to the highly non-linear nature of these processes, the theory experienced a long period of slow development. In recent years there have been a number of important advances in the theory and applications of self-normalized processes. Some of these developments are closely linked to the study of central limit theorems, which imply that self-normalized processes are approximate pivots for statistical inference. The present volume covers recent developments in the area, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales. This is the first book that systematically treats the theory and applications of self-normalization.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aLai, Tze Leung. _eautor _9303667
700	1		_aShao, Qi-Man. _eautor _9335462
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540856351
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-85636-8 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c298852 _d298852