Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Condition: New.
Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In.
Published by LAP LAMBERT Academic Publishing 2015-06-03, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: Chiron Media, Wallingford, United Kingdom
Paperback. Condition: New.
Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: moluna, Greven, Germany
Condition: New.
Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Published by LAP LAMBERT Academic Publishing Jun 2015, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book 'Bayesian analysis: general framework' deals with Bayesian inference within the framework of four stochastic models: the normal random sample, the Gauss-Markov model, the beta-binomial model and the Poisson-gamma model. For each of these models, analytic expressions are presented for the posterior PDF, the prior predictive PDF and the posterior predictive PDF, under the Laplace prior PDF, the Jeffreys prior PDF and the conjugate prior PDF. Topics such as the elicitation of hyper-parameter for the conjugate prior PDF, the selection of models and prediction in multivariate regression analysis and the use of the Bayes factor in the test of hypothesis are dealt with more detail. 156 pp. Englisch.
Published by LAP LAMBERT Academic Publishing Jun 2015, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book 'Bayesian analysis: general framework' deals with Bayesian inference within the framework of four stochastic models: the normal random sample, the Gauss-Markov model, the beta-binomial model and the Poisson-gamma model. For each of these models, analytic expressions are presented for the posterior PDF, the prior predictive PDF and the posterior predictive PDF, under the Laplace prior PDF, the Jeffreys prior PDF and the conjugate prior PDF. Topics such as the elicitation of hyper-parameter for the conjugate prior PDF, the selection of models and prediction in multivariate regression analysis and the use of the Bayes factor in the test of hypothesis are dealt with more detail.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch.
Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659716286 ISBN 13: 9783659716287
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book 'Bayesian analysis: general framework' deals with Bayesian inference within the framework of four stochastic models: the normal random sample, the Gauss-Markov model, the beta-binomial model and the Poisson-gamma model. For each of these models, analytic expressions are presented for the posterior PDF, the prior predictive PDF and the posterior predictive PDF, under the Laplace prior PDF, the Jeffreys prior PDF and the conjugate prior PDF. Topics such as the elicitation of hyper-parameter for the conjugate prior PDF, the selection of models and prediction in multivariate regression analysis and the use of the Bayes factor in the test of hypothesis are dealt with more detail.