Bayesian analysis general framework de casaca joão (14 resultados)

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Taschenbuch. Condición: Neu. Bayesian analysis: general framework | Includes multivariate regression analysis, model selection and response prediction | João Casaca | Taschenbuch | 156 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659716287 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. Bayesian Analysis: General Framework | Includes Multivariate Regression Analysis, Model Selection, and Response Prediction. Second Edition | João Casaca | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209921780 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

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Taschenbuch. Condición: 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.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 156 pp. Englisch.

Taschenbuch. Condición: 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.…

Taschenbuch. Condición: 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch.

Taschenbuch. Condición: 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.…