04870nam a22004215i 4500001001800000003000900018005001700027007001500044008004100059020001800100020001900118024003500137040000900172082001400181100003200195245010100227264004600328300003400374336002600408337002600434338003900460347002400499490004500523505126000568520215701828650001603985650002904001650001604030650003604046710003404082773002004116776003604136830004504172856010304217942001204320999001704332952009904349978-0-387-75971-5DE-He21320260521091954.0cr nn 008mamaa100301s2008    xxu|    s    |||| 0|eng d  a9780387759715  a997803877597157 a10.1007/978-0-387-75971-52doi  cCICY04a519.52231 aDasGupta, Anirban.eauthor.10aAsymptotic Theory of Statistics and Probabilityh[recurso electrónico] /cby Anirban DasGupta. 1aNew York, NY :bSpringer New York,c2008.  aXVII, 724p.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  arecurso en líneabcr2rdacarrier  atext filebPDF2rda1 aSpringer Texts in Statistics,x1431-875X0 aBasic Convergence Concepts and Theorems -- Metrics, Information Theory, Convergence, and Poisson Approximations -- More General Weak and Strong Laws and the Delta Theorem -- Transformations -- More General Central Limit Theorems -- Moment Convergence and Uniform Integrability -- Sample Percentiles and Order Statistics -- Sample Extremes -- Central Limit Theorems for Dependent Sequences -- Central Limit Theorem for Markov Chains -- Accuracy of Central Limit Theorems -- Invariance Principles -- Edgeworth Expansions and Cumulants -- Saddlepoint Approximations -- U-statistics -- Maximum Likelihood Estimates -- M Estimates -- The Trimmed Mean -- Multivariate Location Parameter and Multivariate Medians -- Bayes Procedures and Posterior Distributions -- Testing Problems -- Asymptotic Efficiency in Testing -- Some General Large-Deviation Results -- Classical Nonparametrics -- Two-Sample Problems -- Goodness of Fit -- Chi-square Tests for Goodness of Fit -- Goodness of Fit with Estimated Parameters -- The Bootstrap -- Jackknife -- Permutation Tests -- Density Estimation -- Mixture Models and Nonparametric Deconvolution -- High-Dimensional Inference and False Discovery -- A Collection of Inequalities in Probability, Linear Algebra, and Analysis.  aThis book is an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. The book has 34 chapters over a wide range of topics, nearly 600 exercises for practice and instruction, and another 300 worked out examples. It also includes a large compendium of 300 useful inequalities on probability, linear algebra, and analysis that are collected together from numerous sources, as an invaluable reference for researchers in statistics, probability, and mathematics. It can be used as a graduate text, as a versatile research reference, as a source for independent reading on a wide assembly of topics, and as a window to learning the latest developments in contemporary topics. The book is unique in its detailed coverage of fundamental topics such as central limit theorems in numerous setups, likelihood based methods, goodness of fit, higher order asymptotics, as well as of the most modern topics such as the bootstrap, dependent data, Bayesian asymptotics, nonparametric density estimation, mixture models, and multiple testing and false discovery. It provides extensive bibliographic references on all topics that include very recent publications. Anirban DasGupta is Professor of Statistics at Purdue University. He has also taught at the Wharton School of the University of Pennsylvania, at Cornell University, and at the University of California at San Diego. He has been on the editorial board of the Annals of Statistics since 1998 and has also served on the editorial boards of the Journal of the American Statistical Association, International Statistical Review, and the Journal of Statistical Planning and Inference. He has edited two monographs in the lecture notes monograph series of the Institute of Mathematical Statistics, is a Fellow of the Institute of Mathematical Statistics and has 70 refereed publications on theoretical statistics and probability in major journals. 0aSTATISTICS. 0aMATHEMATICAL STATISTICS.14aSTATISTICS.24aSTATISTICAL THEORY AND METHODS.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780387759708 0aSpringer Texts in Statistics,x1431-875X40uhttp://dx.doi.org/10.1007/978-0-387-75971-5zVer el texto completo en las instalaciones del CICY  2ddccER  c34681d34681  00102ddc40708LEaCICYbCICYcELd2025-07-10l0o519.5r2025-07-10 08:40:23w2025-07-10yER