Heyde Christopher (39 results)

gebundene Ausgabe. Condition: 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.

Condition: 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.

Hardcover. Condition: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.

Condition: New. pp. 252.

Condition: New. pp. 252 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Condition: New. pp. 252.

Condition: 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.

Kartoniert. Condition: Gut. 24 cm XII, 500 S. Orig.-Karton. Mit Abbildungen im Text. Gutes Exemplar.

Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.

Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 62 HEY 9780387226798 Sprache: Englisch Gewicht in Gramm: 550.

Condition: 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.

Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.

Card Cover. Condition: Very Good. 1st Edition. Good With Light Handling Wear On The Covers A Slight Water Mark On The Foredge On Several Preliminaries And Tanned Edges. Pp 92 Illustrations.

Softcover. Condition: Sehr gut. Eine umfassende Sammlung von Aufsätzen zur Zeitgeschichte, die Themen des 20. Jahrhunderts untersucht, einschließlich der politischen und sozialen Entwicklungen in Deutschland und Europa. Zustand: Einband mit geringfügigen Gebrauchsspuren, insgesamt SEHR GUTER Zustand! Stichworte: Genres: Geschichte, Politik, Kulturgeschichte; Schlagworte: Zeitgeschichte, 20. Jahrhundert, Deutschland, NS-Judenverfolgung, Reparationen, Brüssel 1958, Kalter Krieg, Mauerbau, Wirtschaftspolitik, Historische Analysen. 211 Seiten Deutsch 441g.

hardcover. Condition: New. In shrink wrap. Looks like an interesting title!

Paperback. Condition: new. Paperback. 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. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: New.

Hardcover. Condition: new. Hardcover. 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. This book in statistical theory unifies the two important approaches to statistical parameter estimation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New. In.

Condition: New. In.

Hardcover/ Pappband. Condition: Gut. 172 S. Statistics Statistik Cover slightly damaged of a removed label. Guter Zustand/ Good With ill. Ex-Library. ha1064071 Sprache: Englisch Gewicht in Gramm: 600.

Paperback. Condition: Brand New. 246 pages. 9.25x6.10x0.57 inches. In Stock.

Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 252 pp. Englisch.

Taschenbuch. Condition: 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.

Buch. Condition: 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.

Paperback. Condition: Like New. Like New. book.

Paperback. Condition: new. Paperback. 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. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condition: new. Hardcover. 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. This book in statistical theory unifies the two important approaches to statistical parameter estimation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.