04388nam a22005535i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001400172072001600186072002300202082001400225100002800239245007100267264006700338300003400405336002600439337002600465338003600491347002400527490004600551505039300597520218200990650001603172650002503188650002103213650001703234650001903251650001903270650002103289650001603310650002503326650004903351650004003400650001903440650004103459650004003500710003403540773002003574776003603594830004603630856004803676912001403724999001903738952007703757978-0-387-92710-7DE-He21320180115171428.0cr nn 008mamaa130821s2010 xxu| s |||| 0|eng d a97803879271079978-0-387-92710-77 a10.1007/978-0-387-92710-72doi 4aQA276-280 7aPBT2bicssc 7aMAT0290002bisacsh04a519.52231 aThas, Olivier.eauthor.10aComparing Distributionsh[electronic resource] /cby Olivier Thas. 1aNew York, NY :bSpringer New York :bImprint: Springer,c2010. aXVI, 354 p.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda1 aSpringer Series in Statistics,x0172-73970 aOne-Sample Problems -- Preliminaries (Building Blocks) -- Graphical Tools -- Smooth Tests -- Methods Based on the Empirical Distribution Function -- Two-Sample and K-Sample Problems -- Preliminaries (Building Blocks) -- Graphical Tools -- Some Important Two-Sample Tests -- Smooth Tests -- Methods Based on the Empirical Distribution Function -- Two Final Methods and Some Final Thoughts. aComparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing. Whereas the latter includes only formal statistical hypothesis tests for the one-sample and the K-sample problems, this book presents a more general and informative treatment by also considering graphical and estimation methods. A procedure is said to be informative when it provides information on the reason for rejecting the null hypothesis. Despite the historically seemingly different development of methods, this book emphasises the similarities between the methods by linking them to a common theory backbone. This book consists of two parts. In the first part statistical methods for the one-sample problem are discussed. The second part of the book treats the K-sample problem. Many sections of this second part of the book may be of interest to every statistician who is involved in comparative studies. The book gives a self-contained theoretical treatment of a wide range of goodness-of-fit methods, including graphical methods, hypothesis tests, model selection and density estimation. It relies on parametric, semiparametric and nonparametric theory, which is kept at an intermediate level; the intuition and heuristics behind the methods are usually provided as well. The book contains many data examples that are analysed with the cd R-package that is written by the author. All examples include the R-code. Because many methods described in this book belong to the basic toolbox of almost every statistician, the book should be of interest to a wide audience. In particular, the book may be useful for researchers, graduate students and PhD students who need a starting point for doing research in the area of goodness-of-fit testing. Practitioners and applied statisticians may also be interested because of the many examples, the R-code and the stress on the informative nature of the procedures. Olivier Thas is Associate Professor of Biostatistics at Ghent University. He has published methodological papers on goodness-of-fit testing, but he has also published more applied work in the areas of environmental statistics and genomics. 0aStatistics. 0aOperations research. 0aDecision making. 0aData mining. 0aBiostatistics. 0aProbabilities. 0aSocial sciences.14aStatistics.24aStatistics, general.24aProbability Theory and Stochastic Processes.24aMethodology of the Social Sciences.24aBiostatistics.24aData Mining and Knowledge Discovery.24aOperation Research/Decision Theory.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780387927091 0aSpringer Series in Statistics,x0172-739740uhttp://dx.doi.org/10.1007/978-0-387-92710-7 aZDB-2-SMA c369831d369831 001040708EBookaelibbelibd2018-01-15r2018-01-15w2018-01-15yEBOOK