Hardcover. Condition: Used: Good. Book is in very good condition with only few underlined pages. Minor shelf/edge wear. Un-creased spine, binding tight, name written on first page.
Published by Springer, New York, 1996
ISBN 10: 0387948082 ISBN 13: 9780387948089
Hardcover. Condition: Fine. xvi, 448 p. 24 cm. Numerous diagrams and tables. Purple hardcover.
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Condition: very good. Berlin & New York: Springer-Verlag, 1996. Hardcover. xvi. 448 pp. Index. - Contents : After Dinner Remarks: On the Occasion of Seymour Geisser's 65th Birthday, Hsinchu, Taiwan, December 13, 1994 / Marvin Zelen -- Story about Cosimo di Medici / David Lane -- Some Statistical Issues in Forensic DNA Profiling / Seymour Geisser -- Statistical Practice as Argumentation: A Sketch of a Theory of Applied Statistics / James S. Hodges -- Decision Rules and Market Share: Aggregation in an Information Contagion Model / David Lane and Roberta Vescovini -- Bayesian Method of Moments (BMOM) Analysis of Mean and Regression Models / Arnold Zellner -- On the Prediction of Growth Curves / Jack C. Lee and Seymour Geisser -- Predictive Influence in the Log Normal Survival Model / Wesley O. Johnson -- Selecting the Form of Combining Regressions Based on Recursive Prediction Criteria / Kuo-yuan Liang and Keunkwan Ryu -- Multiperiod-Ahead Predictive Densities and Model Comparison in Dynamic Models / Chung-ki Min -- Bayesian Prediction Under Asymmetric Linear Loss: Forecasting State Tax Revenues in Iowa / Charles H. Whiteman -- On Small Sample Bayesian Inference and Sequential Design for Quantal Response Curves / Tom Leonard and John S. J. Hsu -- Some Simulation Results for the Performance of DNA Classification of Noisy Image Data / S. James Press -- Case-Control Studies and Bayesian Inference / M. Zelen and R. A. Parker -- Orthogonalizations and Prior Distributions for Orthogonalized Model Mixing / Merlise Clyde and Giovanni Parmigiani -- Improved Quasi-Maximum Likelihood Estimation for Stochastic Volatility Models / F. Jay Breidt and Alicia L. Carriquiry -- Bayesian Inference for Linear Models Subject to Inequality Constraints / John F. Geweke -- The Asymptotic Distribution of the Maximum Likelihood and Mantel-Haenszel Estimators of the Common Odds Ratio in k 2x2 Tables / Samuel W. Greenhouse and Joseph L. Gastwirth -- On the Justification of Default and Intrinsic Bayes Factors / James O. Berger and Luis R. Pericchi -- Tests on Independence of VNTR Alleles in the Chinese Population in Hong Kong / Wing K. Fung -- Bayes Factors for Testing the Equality of Covariance Matrix Eigenvalues / Robert E. McCulloch and Peter E. Rossi -- Model Selection in Parapsychology: Psychokinesis, Precognition or Chance / Jessica Utts -- An Empirical Bayesian Approach to Cointegrating Rank Selection and Test of the Present Value Model for Stock Prices / John C. Chao and Peter C. B. Phillips -- Prediction of Individual Bond Prices via the TDM Model / Takeaki Kariya and Hiroshi Tsuda -- On the Use of Canonical Correlation Analysis in Testing Common Trends / N. H. Chan and Ruey S. Tsay -- Conjugate Processes / Clive W. J. Granger and Jin-Lung Lin -- Nonlinear Time Series-Bifurcation, Chaos and Stationarity / Wolfgang Kliemann -- The VAR-VARCH Model: A Bayesian Approach / Wolfgang Polasek and Hideo Kozumi -- Statistical Assessment of Atmospheric Ozone Data for Depletion / Gregory C. Reinsel and G. C. Tiao. Condition : very good copy. ISBN 9780387948089. Keywords : MATHEMATICS, statistics.
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Condition: New. pp. 468.
Condition: Used. pp. 448.
Condition: Used. pp. 448.
Paperback. Condition: Brand New. reprint edition. 464 pages. 9.25x6.10x1.34 inches. In Stock.
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: Used. pp. 448.
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Taschenbuch. Condition: Neu. Modelling and Prediction Honoring Seymour Geisser | Jack C. Lee (u. a.) | Taschenbuch | xvi | Englisch | 2012 | Springer | EAN 9781461275299 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Modelling and Prediction Honoring Seymour Geisser contains the refereed proceedings of the Conference on Forecasting, Prediction, and Modelling held at National Chiao Tung University, Taiwan in 1994. The papers discuss general methodological issues; prediction; design of experiments and classification; prior distributions and estimation; posterior odds, testing, and model selection; modelling and prediction in finance; and time series modelling and applications. Specific topics include very interesting and topical statistical issues related to DNA fingerprinting and spatial image reconstruction, foundational issues for applied statistics and testing hypotheses, forecasting tax revenues and bond prices, and assessing oxone depletion.
Condition: New.
Language: English
Published by Taylor & Francis Group, 2010
ISBN 10: 1439803544 ISBN 13: 9781439803547
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Condition: New. PP. 516 Index.
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Language: English
Published by Taylor & Francis Group, 2010
ISBN 10: 1439803544 ISBN 13: 9781439803547
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Condition: New. PP. 516.
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Language: English
Published by John Wiley and Sons Inc, US, 2006
ISBN 10: 0471667269 ISBN 13: 9780471667261
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Add to basketHardback. Condition: New. A fascinating investigation into the foundations of statistical inference This publication examines the distinct philosophical foundations of different statistical modes of parametric inference. Unlike many other texts that focus on methodology and applications, this book focuses on a rather unique combination of theoretical and foundational aspects that underlie the field of statistical inference. Readers gain a deeper understanding of the evolution and underlying logic of each mode as well as each mode's strengths and weaknesses. The book begins with fascinating highlights from the history of statistical inference. Readers are given historical examples of statistical reasoning used to address practical problems that arose throughout the centuries. Next, the book goes on to scrutinize four major modes of statistical inference: * Frequentist * Likelihood * Fiducial * Bayesian The author provides readers with specific examples and counterexamples of situations and datasets where the modes yield both similar and dissimilar results, including a violation of the likelihood principle in which Bayesian and likelihood methods differ from frequentist methods. Each example is followed by a detailed discussion of why the results may have varied from one mode to another, helping the reader to gain a greater understanding of each mode and how it works. Moreover, the author provides considerable mathematical detail on certain points to highlight key aspects of theoretical development. The author's writing style and use of examples make the text clear and engaging. This book is fundamental reading for graduate-level students in statistics as well as anyone with an interest in the foundations of statistics and the principles underlying statistical inference, including students in mathematics and the philosophy of science. Readers with a background in theoretical statistics will find the text both accessible and absorbing.
Condition: New. pp. xv + 192 Illus.
Hardcover. Condition: Brand New. 1st edition. 498 pages. 10.75x7.50x1.25 inches. In Stock.
Condition: New. pp. xv + 192 Index.
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 1439800081 ISBN 13: 9781439800089
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Hardcover. Condition: Brand New. 1st edition. 192 pages. 9.50x6.25x0.75 inches. In Stock.
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 1439800081 ISBN 13: 9781439800089
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Hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Language: English
Published by John Wiley and Sons Inc, US, 2006
ISBN 10: 0471667269 ISBN 13: 9780471667261
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Add to basketHardback. Condition: New. A fascinating investigation into the foundations of statistical inference This publication examines the distinct philosophical foundations of different statistical modes of parametric inference. Unlike many other texts that focus on methodology and applications, this book focuses on a rather unique combination of theoretical and foundational aspects that underlie the field of statistical inference. Readers gain a deeper understanding of the evolution and underlying logic of each mode as well as each mode's strengths and weaknesses. The book begins with fascinating highlights from the history of statistical inference. Readers are given historical examples of statistical reasoning used to address practical problems that arose throughout the centuries. Next, the book goes on to scrutinize four major modes of statistical inference: * Frequentist * Likelihood * Fiducial * Bayesian The author provides readers with specific examples and counterexamples of situations and datasets where the modes yield both similar and dissimilar results, including a violation of the likelihood principle in which Bayesian and likelihood methods differ from frequentist methods. Each example is followed by a detailed discussion of why the results may have varied from one mode to another, helping the reader to gain a greater understanding of each mode and how it works. Moreover, the author provides considerable mathematical detail on certain points to highlight key aspects of theoretical development. The author's writing style and use of examples make the text clear and engaging. This book is fundamental reading for graduate-level students in statistics as well as anyone with an interest in the foundations of statistics and the principles underlying statistical inference, including students in mathematics and the philosophy of science. Readers with a background in theoretical statistics will find the text both accessible and absorbing.
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