Displaying similar documents to “Bayesian reference analysis for proportional hazards model of random censorship with Weibull distribution”

Bayesian estimation of the intraclass correlation coefficients in the mixed linear model

Teresa H. Jelenkowska (1998)

Applications of Mathematics

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The method of determining Bayesian estimators for the special ratios of variance components called the intraclass correlation coefficients is presented. The exact posterior distribution for these ratios of variance components is obtained. The approximate posterior mean of this distribution is also derived. All computations are non-iterative and avoid numerical integration.

A Bayesian look at nuisance parameters.

A. Philip Dawid (1980)

Trabajos de Estadística e Investigación Operativa

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The elimination of nuisance parameters has classically been tackled by various ad hoc devices, and has led to a number of attemps to define partial sufficiency and ancillarity. The Bayesian approach is clearly defined. This paper examines some classical procedures in order to see when they can be given a Bayesian justification.

Likelihood and the Bayes procedure.

Hirotugu Akaike (1980)

Trabajos de Estadística e Investigación Operativa

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In this paper the likelihood function is considered to be the primary source of the objectivity of a Bayesian method. The necessity of using the expected behaviour of the likelihood function for the choice of the prior distribution is emphasized. Numerical examples, including seasonal adjustment of time series, are given to illustrate the practical utility of the common-sense approach to Bayesian statistics proposed in this paper.

On the frequentist and Bayesian approaches to hypothesis testing.

Elías Moreno, F. Javier Girón (2006)

SORT

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Hypothesis testing is a model selection problem for which the solution proposed by the two main statistical streams of thought, frequentists and Bayesians, substantially differ. One may think that this fact might be due to the prior chosen in the Bayesian analysis and that a convenient prior selection may reconcile both approaches. However, the Bayesian robustness viewpoint has shown that, in general, this is not so and hence a profound disagreement between both approaches exists. In...

Likelihood for random-effect models (with discussion).

Youngjo Lee, John A. Nelder (2005)

SORT

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For inferences from random-effect models Lee and Nelder (1996) proposed to use hierarchical likelihood (h-likelihood). It allows influence from models that may include both fixed and random parameters. Because of the presence of unobserved random variables h-likelihood is not a likelihood in the Fisherian sense. The Fisher likelihood framework has advantages such as generality of application, statistical and computational efficiency. We introduce an extended likelihood framework and...

Sequential learning, discontinuities and changes: Discussion.

Stephen E. Fienberg, José M. Bernardo, Philip J. Brown, A. Philip Dawid, James M. Dickey, Joseph B. Kadane, Tom Leonard (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Makov, Udi E., Approximation of unsupervised Bayes learning procedures, Smith, Adrian F. M., Change-Point problems: approaches and applications and by Harrison, P. J. and Smith Jim Q., Discontinuity, decision and conflict, the three of them part of a round table on Sequential learning, discontinuities and changes held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).