Statistical Theory and Inference

David J. Olive

ISBN 10: 331937589X / ISBN 13: 9783319375892

Verlag: Springer International Publishing, Springer Nature Switzerland Sep 2016, 2016

Beschreibung

Neuware -This text is fora one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families.Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name' distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 448 pp. Englisch.

Bestandsnummer des Verkäufers 9783319375892

Bibliografische Details

• Titel: Statistical Theory and Inference
• Verlag: Springer International Publishing, Springer Nature Switzerland Sep 2016
• Erscheinungsjahr: 2016
• Sprache: Englisch
• ISBN-10: 331937589X
• ISBN-13: 9783319375892
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 25 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 25 mm
• Gewicht: 674 Gramm

Über diesen Titel

Inhaltsangabe

This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families.

Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name" distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.

Über die Autorin bzw. den Autor

David Olive is an Associate Professor in the Department of Mathematics at Southern Illinois University.