Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 59,71
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Aggiungi al carrelloCondizione: New. In.
EUR 55,94
Quantità: 10 disponibili
Aggiungi al carrelloPF. Condizione: New.
Da: Revaluation Books, Exeter, Regno Unito
EUR 77,70
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 1990 edition. 212 pages. 9.60x6.69x0.55 inches. In Stock.
Editore: Springer Berlin Heidelberg, 1990
ISBN 10: 3540530800 ISBN 13: 9783540530800
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 53,49
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This introduction to Bayesian inference places special emphasis on applications. All basic concepts are presented: Bayes' theorem, prior density functions, point estimation, confidence region, hypothesis testing and predictive analysis. In addition, Monte Carlo methods are discussed since the applications mostly rely on the numerical integration of the posterior distribution. Furthermore, Bayesian inference in the linear model, nonlinear model, mixed model and in the model with unknown variance and covariance components is considered. Solutions are supplied for the classification, for the posterior analysis based on distributions of robust maximum likelihood type estimates, and for the reconstruction of digital images.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 104,58
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Editore: Springer Berlin Heidelberg, 1990
ISBN 10: 3540530800 ISBN 13: 9783540530800
Lingua: Inglese
Da: Buchpark, Trebbin, Germania
EUR 42,18
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Okt 1990, 1990
ISBN 10: 3540530800 ISBN 13: 9783540530800
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 53,49
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This introduction to Bayesian inference places special emphasis on applications. All basic concepts are presented: Bayes' theorem, prior density functions, point estimation, confidence region, hypothesis testing and predictive analysis. In addition, Monte Carlo methods are discussed since the applications mostly rely on the numerical integration of the posterior distribution. Furthermore, Bayesian inference in the linear model, nonlinear model, mixed model and in the model with unknown variance and covariance components is considered. Solutions are supplied for the classification, for the posterior analysis based on distributions of robust maximum likelihood type estimates, and for the reconstruction of digital images. 212 pp. Englisch.
Editore: Springer Berlin Heidelberg, 1990
ISBN 10: 3540530800 ISBN 13: 9783540530800
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 48,37
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This introduction to Bayesian inference places special emphasis on applications. All basic concepts are presented: Bayes theorem, prior density functions, point estimation, confidence region, hypothesis testing and predictive analysis. In addition, Monte C.
Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Okt 1990, 1990
ISBN 10: 3540530800 ISBN 13: 9783540530800
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 53,49
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This introduction to Bayesian inference places special emphasis on applications. All basic concepts are presented: Bayes' theorem, prior density functions, point estimation, confidence region, hypothesis testing and predictive analysis. In addition, Monte Carlo methods are discussed since the applications mostly rely on the numerical integration of the posterior distribution. Furthermore, Bayesian inference in the linear model, nonlinear model, mixed model and in the model with unknown variance and covariance components is considered. Solutions are supplied for the classification, for the posterior analysis based on distributions of robust maximum likelihood type estimates, and for the reconstruction of digital images.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 212 pp. Englisch.