gebundene Ausgabe. Zustand: Gut. 235 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 510.
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
EUR 19,07
Anzahl: 1 verfügbar
In den WarenkorbZustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9780387982250.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 34,59
Anzahl: 4 verfügbar
In den WarenkorbZustand: New. pp. 252 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
Anbieter: Studio Books and Music, CAMBRIDGE, Vereinigtes Königreich
EUR 35,70
Anzahl: 1 verfügbar
In den WarenkorbIn mint condition.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
24 cm. original hardcover. x,236 pp. references. index. "Springer Series in Statistics". -very good. 777g.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 114,40
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is concerned with the general theory of optimal estimation of - rameters in systems subject to random e ects and with the application of this theory. The focus is on choice of families of estimating functions, rather than the estimators derived therefrom, and on optimization within these families. Only assumptions about means and covariances are required for an initial d- cussion. Nevertheless, the theory that is developed mimics that of maximum likelihood, at least to the rst order of asymptotics. The term quasi-likelihood has often had a narrow interpretation, asso- ated with its application to generalized linear model type contexts, while that of optimal estimating functions has embraced a broader concept. There is, however, no essential distinction between the underlying ideas and the term quasi-likelihood has herein been adopted as the general label. This emphasizes its role in extension of likelihood based theory. The idea throughout involves nding quasi-scores from families of estimating functions. Then, the qua- likelihood estimator is derived from the quasi-score by equating to zero and solving, just as the maximum likelihood estimator is derived from the like- hood score.