Displaying similar documents to “Bayesian density estimation.”

Bayesian non-parametric theory: Discussion.

Irving John Good, Joseph B. Kadane, Tom Leonard, Anthony O'Hagan, Adrian F. M. Smith (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the paper by Dalal, Sid R., Nonparametric Bayes decision theory, part of a round table on Bayesian non-parametric theory held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Nonparametric Bayes decision theory.

Sid R. Dalal (1980)

Trabajos de Estadística e Investigación Operativa

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A summary of the seminar with the same title is presented. Ferguson's fundamental work on the theory of Dirichlet processes is elucidated and their shortcomings are discussed. Some modifications are also proposed and illustrated. Some of the intrincate mathematical issues related to the definitions and the proofs are not discussed for the sake of clarity and brevity. The development related to unimodal processes, briefly mentioned in the last section, will appear as a joint work with...

Some history of the hierarchical Bayesian methodology.

Irving John Good (1980)

Trabajos de Estadística e Investigación Operativa

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A standard tecnique in subjective Bayesian methodology is for a subject (you) to make judgements of the probabilities that a physical probability lies in various intervals. In the Bayesian hierarchical technique you make probability judgements (of a higher type, order, level or stage) concerning the judgements of lower type. The paper will outline some of the history of this hierarchical technique with emphasis on the contributions by I. J. Good because I have read every word written...

Cross additivity - an application

Sandra Saraiva Ferreira, Dário Ferreira, João Tiago Mexia (2006)

Discussiones Mathematicae Probability and Statistics

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We try to show that Discriminant Analysis can be considered as a branch of Statistical Decision Theory when viewed from a Bayesian approach. First we present the necessary measure theory results, next we briefly outline the foundations of Bayesian Inference before developing Discriminant Analysis as an application of Bayesian Estimation. Our approach renders Discriminant Analysis more flexible since it gives the possibility of classing an element as belonging to a group of populations....

On the Bayesian estimation for the stationary Neyman-Scott point processes

Jiří Kopecký, Tomáš Mrkvička (2016)

Applications of Mathematics

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The pure and modified Bayesian methods are applied to the estimation of parameters of the Neyman-Scott point process. Their performance is compared to the fast, simulation-free methods via extensive simulation study. Our modified Bayesian method is found to be on average 2.8 times more accurate than the fast methods in the relative mean square errors of the point estimates, where the average is taken over all studied cases. The pure Bayesian method is found to be approximately as good...