Geometrical Foundations of Asymptotic Inference
2011 оны 9-р сар · John Wiley & Sons
4.0star
2 шүүмжreport
Электрон ном
376
Хуудас
reportҮнэлгээ болон шүүмжийг баталгаажуулаагүй Нэмэлт мэдээлэл авах
Энэ электрон номын тухай
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
Үнэлгээ, сэтгэгдэл
4.0
2 шүүмж
Зохиогчийн тухай
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.
Энэ электрон номыг үнэлэх
Санал бодлоо хэлнэ үү.
Унших мэдээлэл
Ухаалаг утас болон таблет
Андройд болон iPad/iPhone-д Google Ном Унших аппыг суулгана уу. Үүнийг таны бүртгэлд автоматаар синк хийх бөгөөд та хүссэн газраасаа онлайн эсвэл офлайнаар унших боломжтой.
Зөөврийн болон ердийн компьютер
Та компьютерийн веб хөтчөөр Google Play-с авсан аудио номыг сонсох боломжтой.
eReaders болон бусад төхөөрөмжүүд
Kobo Цахим ном уншигч гэх мэт e-ink төхөөрөмжүүд дээр уншихын тулд та файлыг татаад төхөөрөмж рүүгээ дамжуулах шаардлагатай болно. Файлуудаа дэмжигддэг Цахим ном уншигч руу шилжүүлэхийн тулд Тусламжийн төвийн дэлгэрэнгүй зааварчилгааг дагана уу.
