Displaying similar documents to “Predictive sample reuse techniques for censored data.”

Predictive sample reuse: Discussion.

Irwin Guttman, S. James Press (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the paper by Geisser, Seymour, Predictive sample reuse techniques for censored data, part of a round table on Bayesian and non-Bayesian conditional inference held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Bayesian and non-Bayesian conditional inference: Discussion.

A. Philip Dawid, Morris H. DeGroot, James M. Dickey, Irving John Good, Bruce M. Hill, Joseph B. Kadane, Tom Leonard, Dennis B. Lindley, Arnold Zellner (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the paper by Barnard, George A., Pivotal inference and the Bayesian controversy, part of a round table on Bayesian and non-Bayesian conditional inference held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Hypothesis testing: Discussion.

Edwin T. Jaynes, David J. Spiegelhalter, Hirotugu Akaike, Arthur P. Dempster, James M. Dickey, Seymour Geisser, Irving John Good, Dennis V. Lindley, Anthony O'Hagan, Arnold Zellner (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Zellner, Arnold and Siow, Aloysius, Posterior odds ratios for selected regression hypotheses and by Bernardo, José M., A Bayesian analysis of classical hypotheses testing, both of them part of a round table on Hypothesis testing held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Outliers in circular data: a Bayesian approach.

Gonzalo Arnaiz Tovar, Carmen Ruiz Rivas (1986)

Qüestiió

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The problem of outliers in circular data is studied from a Bayesian point of view. Susprising observations are identified by means of a predictive measure. On the basis of Box-Tiao methodology, the mean-shift model and some aspects of the contamination of the concentration parameter for a Von Mises distribution are analyzed. Intuitive aspects of the resultant weights and their applications in some classical examples are included.

Likelihood, sufficiency and ancillarity: Discussion.

George A. Barnard, P. R. Freeman, Daniel Peña, James M. Dickey, Seymour Geisser, Dennis V. Lindley, Anthony O'Hagan, Adrian F. M. Smith (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Akaike, Hirotugu, Likelihood and the Bayes procedure and by Dawid, A. Philip, A Bayesian look at nuisance parameters, both of them part of a round table on Likelihood, sufficiency and ancillarity held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Bayesian joint modelling of the mean and covariance structures for normal longitudinal data.

Edilberto Cepeda-Cuervo, Vicente Nunez-Anton (2007)

SORT

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We consider the joint modelling of the mean and covariance structures for the general antedependence model, estimating their parameters and the innovation variances in a longitudinal data context. We propose a new and computationally efficient classic estimation method based on the Fisher scoring algorithm to obtain the maximum likelihood estimates of the parameters. In addition, we also propose a new and innovative Bayesian methodology based on the Gibbs sampling, properly adapted for...

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.

The roles of inductive modelling and coherence in Bayesian statistics.

Tom Leonard (1980)

Trabajos de Estadística e Investigación Operativa

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The role of the inductive modelling process (IMP) seems to be of practical importance in Bayesian statistics; it is recommended that the statistician should emphasize meaningful real-life considerations rather than more formal aspects such as the axioms of coherence. It is argued that whilst axiomatics provide some motivation for the Bayesian philosophy, the real strength of Bayesianism lies in its practical advantages and its plausible representation of real-life processes. A number...