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Probability Matching Priors: Higher Order Asymptotics: 178 (Lecture Notes in Statistics, 178) - Softcover
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Probability matching priors, ensuring frequentist validity of posterior credible sets up to the desired order of asymptotics, are of substantial current interest. They can form the basis of an objective Bayesian analysis. In addition, they provide a route for obtaining accurate frequentist confidence sets, which are meaningful also to a Bayesian. This monograph presents, for the first time in book form, an up-to-date and comprehensive account of probability matching priors addressing the problems of both estimation and prediction. Apart from being useful to researchers, it can be the core of a one-semester graduate course in Bayesian asymptotics. Gauri Sankar Datta is a professor of statistics at the University of Georgia. He has published extensively in the fields of Bayesian analysis, likelihood inference, survey sampling, and multivariate analysis. Rahul Mukerjee is a professor of statistics at the Indian Institute of Management Calcutta. He co-authored three other research monographs, including "A Calculus for Factorial Arrangements" in this series. A fellow of the Institute of Mathematical Statistics, Dr. Mukerjee is on the editorial boards of several international journals.
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Probability matching priors, ensuring frequentist validity of posterior credible sets up to the desired order of asymptotics, are of substantial current interest. They can form the basis of an objective Bayesian analysis. In addition, they provide a route for obtaining accurate frequentist confidence sets, which are meaningful also to a Bayesian. This monograph presents, for the first time in book form, an up-to-date and comprehensive account of probability matching priors addressing the problems of both estimation and prediction. Apart from being useful to researchers, it can be the core of a one-semester graduate course in Bayesian asymptotics.
Gauri Sankar Datta is a professor of statistics at the University of Georgia. He has published extensively in the fields of Bayesian analysis, likelihood inference, survey sampling, and multivariate analysis.
Rahul Mukerjee is a professor of statistics at the Indian Institute of Management Calcutta. He co-authored three other research monographs, including A Calculus for Factorial Arrangements in this series. A fellow of the Institute of Mathematical Statistics, Dr. Mukerjee is on the editorial boards of several international journals.
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Probability Matching Priors: Higher Order Asymptotics.
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X, 127 p. Paperback Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. 2 Lecture Notes in Statistics, Vol. 178 Sprache: Englisch. Artikel-Nr. 329GB
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Probability Matching Priors: Higher Order Asymptotics (Lecture Notes in Statistics, 178)
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Probability Matching Priors
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Springer-Verlag New York Inc., 2004
ISBN 10: 038720329X
ISBN 13: 9780387203294
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Zustand: New. Covers the topic of probability matching priors. This book is suitable for researchers, Bayesian and frequentist; and graduate students in Statistics. Series: Lecture Notes in Statistics. Num Pages: 137 pages, 2 black & white illustrations, biography. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 7. Weight in Grams: 240. . 2004. Softcover reprint of the original 1st ed. 2004. Paperback. . . . . Books ship from the US and Ireland. Artikel-Nr. V9780387203294
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Probability Matching Priors: Higher Order Asymptotics
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Paperback. Zustand: Brand New. 1st edition. 127 pages. 9.00x6.00x0.50 inches. In Stock. Artikel-Nr. x-038720329X
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Probability Matching Priors: Higher Order Asymptotics
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Springer New York, Springer New York, 2004
ISBN 10: 038720329X
ISBN 13: 9780387203294
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Probability matching priors, ensuring frequentist validity of posterior credible sets up to the desired order of asymptotics, are of substantial current interest. They can form the basis of an objective Bayesian analysis. In addition, they provide a route for obtaining accurate frequentist confidence sets, which are meaningful also to a Bayesian. This monograph presents, for the first time in book form, an up-to-date and comprehensive account of probability matching priors addressing the problems of both estimation and prediction. Apart from being useful to researchers, it can be the core of a one-semester graduate course in Bayesian asymptotics.Gauri Sankar Datta is a professor of statistics at the University of Georgia. He has published extensively in the fields of Bayesian analysis, likelihood inference, survey sampling, and multivariate analysis.Rahul Mukerjee is a professor of statistics at the Indian Institute of Management Calcutta. He co-authored three other research monographs, including 'A Calculus for Factorial Arrangements' in this series. A fellow of the Institute of Mathematical Statistics, Dr. Mukerjee is on the editorial boards of several international journals. Artikel-Nr. 9780387203294
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