The implementation of the bayesian paradigm

Abstract

Routine implementation of the Bayesian paradigm requires an efficient approach to the calculation and display of posterior or predictive distributions for given likelihood and prior specifi- cations. In this paper we shall review some of the analytic and numerical approaches currently available, describing in detail a numerical integration strategy based on Gaussian quadrature, and an associated strategy for the reconstruction and display of distributions based on spline techniques.

Keywords

Bayesian probabilityComputer scienceNumerical integrationGaussianPosterior probabilityGaussian quadratureAlgorithmMachine learningArtificial intelligenceMathematicsNyström methodPhysicsIntegral equation

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Publication Info

Year: 1985
Type: article
Volume: 14
Issue: 5
Pages: 1079-1102
Citations: 110
Access: Closed

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APA Style

                            
                                
                                    A. F. M. Smith, 
                                
                                    A. M. Skene, 
                                
                                    J.E. Shaw
                                
                                et al.
                            
                            (1985). 
                            The implementation of the bayesian paradigm. 
                            Communication in Statistics- Theory and Methods
                            , 14
                            (5)
                            , 1079-1102.
                            https://doi.org/10.1080/03610928508828963
                        

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DOI: 10.1080/03610928508828963