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  • 1 Statistical preliminaries 1; 2 Bayesian inference and decision theory 29; 3 Utility, prior, and Bayesian robustness 65; 4 Large sample methods 99; 5 Choice of priors for low-dimensional parameters 121; 6 Hypothesis testing and model selection 159; 7 Bayesian computations 205; 8 Some common problems in inference 239; 9 High-dimensional problems 255; 10 Some applications 289; A Common statistical densities 303; B Birnbaum's theorem on likelihood principle 307; C Coherence 311; D Microarray 313; E Bayes sufficiency 315 (xsd:string)
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  • 2006 (xsd:gyear)
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  • 2006 (xsd:gyear)
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  • Englisch (EN) (xsd:string)
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  • 9780387400846 ()
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  • An introduction to Bayesian analysis : theory and methods (xsd:string)
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  • book (en)
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  • GESIS-BIB (xsd:string)
  • New York: Springer, 2006.- 352 S., graph. Darst. (xsd:string)
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