Geometrical Foundations of Asymptotic Inference
sep. 2011 · John Wiley & Sons
4,0star
2 anmeldelserreport
E-bok
376
Sider
reportVurderinger og anmeldelser blir ikke kontrollert Finn ut mer
Om denne e-boken
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
* 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
Vurderinger og anmeldelser
4,0
2 anmeldelser
Om forfatteren
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.
Vurder denne e-boken
Fortell oss hva du mener.
Hvordan lese innhold
Smarttelefoner og nettbrett
Installer Google Play Bøker-appen for Android og iPad/iPhone. Den synkroniseres automatisk med kontoen din og lar deg lese både med og uten nett – uansett hvor du er.
Datamaskiner
Du kan lytte til lydbøker du har kjøpt på Google Play, i nettleseren på datamaskinen din.
Lesebrett og andre enheter
For å lese på lesebrett som Kobo eReader må du laste ned en fil og overføre den til enheten din. Følg den detaljerte veiledningen i brukerstøtten for å overføre filene til støttede lesebrett.
