Displaying similar documents to “A sequential Bayesian approach to estimating the dimension of a multinomial distribution”

Improving predictive distributions.

Morris H. DeGroot (1980)

Trabajos de Estadística e Investigación Operativa

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Consider a sequence of decision problems S, S, ... and suppose that in problem S the statistician must specify his predictive distribution F for some random variable X and make a decision based on that distribution. For example, X might be the return on some particular investment and the statistician must decide whether or not to make that investment. The random variables X, X, ... are assumed to be independent and completely unrelated. It is also assumed that each predictive distribution...

Unimodal contaminations in testing point null hypothesis.

Miguel Angel Gómez-Villegas, Luís Sanz (2003)

RACSAM

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The problem of testing a point null hypothesis from the Bayesian perspective is considered. The uncertainties are modelled through use of ε?contamination class with the class of contaminations including: i) All unimodal distributions and ii) All unimodal and symmetric distributions. Over these classes, the infimum of the posterior probability of the point null hypothesis is computed and compared with the p?value and a better approach than the one known is obtained.

Three methods for constructing reference prior distributions.

Eusebio Gómez Sánchez-Manzano, Miguel A. Gómez Villegas (1990)

Revista Matemática de la Universidad Complutense de Madrid

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Three methods are proposed for constructing reference prior densities for certain biparametric distribution families. These densities represent approximations to the Bayesian concept of noninformative distribution.

Sequential estimation of survival functions with a neutral to the right process prior

Domingo Morales, Leandro Pardo, Vicente Quesada (1994)

Applications of Mathematics

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In this work, a parametric sequential estimation method of survival functions is proposed in the Bayesian nonparametric context when neutral to the right processes are used. It is proved that the mentioned method is an 1-SLA rule when Dirichlet processes are used; furthermore, asymptotically pointwise optimal procedures are obtained. Finally, an example is given.