Die asymptotische Interferenz ist ein wichtiges statistisches Problem. Eine geometrische Formulierung ausgehend von einem einfache, präzisen und konzeptuellen Ansatz stellen die Autoren dieses Buches vor.
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ROBERT E. KASS is Professor and Head of the Department of Statistics at Carnegie Mellon University. PAUL W. VOS is Associate Professor of Biostatistics at East Carolina University. Both authors received their PhDs from the University of Chicago.
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Hardcover. Etat : new. Hardcover. Differential geometry provides an aesthetically appealing and oftenrevealing view of statistical inference. Beginning with anelementary treatment of one-parameter statistical models and endingwith an overview of recent developments, this is the first book toprovide an introduction to the subject that is largely accessibleto readers not already familiar with differential geometry. It alsogives a streamlined entry into the field to readers with richermathematical backgrounds. Much space is devoted to curvedexponential families, which are of interest not only because theymay be studied geometrically but also because they are analyticallyconvenient, so that results may be derived rigorously. In addition,several appendices provide useful mathematical material on basicconcepts in differential geometry. Topics covered include thefollowing: * Basic properties of curved exponential families * Elements of second-order, asymptotic theory * The Fisher-Efron-Amari theory of information loss and recovery * Jeffreys-Rao information-metric Riemannian geometry * Curvature measures of nonlinearity * Geometrically motivated diagnostics for exponential familyregression * Geometrical theory of divergence functions * A classification of and introduction to additional work in thefield This book provides a thorough introduction to asymptotic inference. It begins with an elementary treatment of one--parameter statistical models and goes on to discuss basic properties of curved exponential families, the Fisher--Efron--Amari theory and Jeffreys--Rao Riemannian geometry based on Fisher information. It also provides an overview of recent developments in the field. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780471826682
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Etat : New. This book provides a thorough introduction to asymptotic inference. It begins with an elementary treatment of one-parameter statistical models and goes on to discuss basic properties of curved exponential families, the Fisher-Efron-Amari theory and Jeffreys-Rao Riemannian geometry based on Fisher information. Series: Wiley Series in Probability and Statistics. Num Pages: 356 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 239 x 161 x 30. Weight in Grams: 766. . 1997. 1st Edition. hardcover. . . . . N° de réf. du vendeur V9780471826682
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