Geometrical Foundations of Asymptotic Inference

July 17, 1997|
Geometrical Foundations of Asymptotic Inference by Robert E. Kass
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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
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.
Title:Geometrical Foundations of Asymptotic InferenceFormat:HardcoverProduct dimensions:376 pages, 9.29 X 6.3 X 1.27 inShipping dimensions:376 pages, 9.29 X 6.3 X 1.27 inPublished:July 17, 1997Publisher:WileyLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0471826685

ISBN - 13:9780471826682

Appropriate for ages: All ages

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