MARC Record from marc_columbia

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001 15123792
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008 170717t20172017flu ob 001 0 eng d
035 $a(OCoLC)ocn993968257
035 $a(NNC)15123792
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019 $a1001265844$a1015204573$a1023531703
020 $a9781315119472$q(electronic bk.)
020 $a1315119471$q(electronic bk.)
020 $z9781498706667
020 $z1498706665
020 $z9781498706643$q(print)
020 $z1498706649$q(print)
020 $z1351645781
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020 $a1351645781$q(EPUB)
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100 1 $aLey, Christophe,$eauthor.
245 10 $aModern directional statistics /$cChristophe Ley, Thomas Verdebout.
264 1 $aBoca Raton, FL :$bCRC Press,$c[2017]
264 4 $c©2017
300 $a1 online resource (xiv, 176 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aChapman & Hall/CRC Interdisciplinary Statistics Series
520 2 $a"Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory. The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory, high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics and the study of asymptotic approximations via Stein's Method. His achievements include the Marie-Jeanne Laurent-Duhamel prize of the Société Française de Statistique and an elected membership at the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis and Econometrics and Statistics. Thomas Verdebout is professor of mathematical statistics at Université libre de Bruxelles (ULB). His main research interests are semi-parametric statistics, high- dimensional statistics, directional statistics and rank-based procedures. He has won an annual prize of the Belgian Academy of Sciences and is an elected member of the International Statistical Institute. He is associate editor for the journals Statistics and Probability Letters and Journal of Multivariate Analysis."--Provided by publisher.
504 $aIncludes bibliographical references and index.
505 0 $aIntroduction -- Advances in flexible parametric distribution theory -- Advances in kernel density estimation on directional supports -- Computational and graphical methods -- Local asymptotic normality for directional data -- Recent results for tests of uniformity and symmetry -- High-dimensional directional statistics.
588 0 $aPrint version record.
650 0 $aStatistics.
650 0 $aMultivariate analysis.
650 6 $aAnalyse multivariée.
650 07 $aMATHEMATICS$xProbability & Statistics$xGeneral.$2bisacsh
650 07 $aSCIENCE$xLife Sciences$xBiology$xGeneral.$2bisacsh
650 7 $aMATHEMATICS$xApplied.$2bisacsh
650 7 $aMATHEMATICS$xProbability & Statistics$xGeneral.$2bisacsh
650 7 $aMultivariate analysis.$2fast$0(OCoLC)fst01029105
650 7 $aStatistics.$2fast$0(OCoLC)fst01132103
655 0 $aElectronic books.
655 4 $aElectronic books.
700 1 $aVerdebout, Thomas,$eeditor.
776 08 $iPrint version:$aLey, Christophe.$tModern directional statistics.$dBoca Raton, FL : CRC Press, Taylor & Francis Group, [2017]$z9781498706643$w(OCoLC)1006594245
830 0 $aInterdisciplinary statistics.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15123792$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS