Statistical Theory and Inference
Language: English
Published by Springer, Palgrave Macmillan Mai 2014, 2014
- Hardcover
- New
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This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 448 pp. Englisch.…
Seller Inventory # 9783319049717
- Title
- Statistical Theory and Inference
- Author
- David J. Olive
- Publisher
- Springer, Palgrave Macmillan Mai 2014
- Publication year
- 2014
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3319049712
- ISBN 13
- 9783319049717
- Item weight
- 834 grams
- Dimensions
- 241x160x30 mm
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.
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buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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