Displaying similar documents to “Misclassified multinomial data: a Bayesian approach.”

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...

On not being rational.

I. Richard Savage (1980)

Trabajos de Estadística e Investigación Operativa

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A Bayesian decision-theoretic approach appears to me as a sensible idealization of a guide to behaviour. At the same time i would like to understand why my behaviour is not always of this form: I sometimes use randomization and I sometimes find confidence intervals acceptable. Not all of my problems have an explicit cost function. Am I lazy or irrational? Do I use non-Bayesian conventions to help communicate? Is the cost of rationality-computation missing from the Bayesian model? ...

Sensitivity to models: Discussion.

William F. Eddy, Anthony O'Hagan, José M. Bernardo, Philip J. Brown, A. Philip Dawid, James M. Dickey, Irving John Good, Adrian F. M. Smith (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Freeman, Peter R., On the number of outliers in data from a linear model and by Box, George E. P., Sampling inference, Bayes' inference and robustness in the advancement of learning, both of them part of a round table on Sensitivity to models 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...

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 inference in applied statistics.

Arthur P. Dempster (1980)

Trabajos de Estadística e Investigación Operativa

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The task of assessing posterior distributions from noisy empirical data imposes difficult requirements of modelling, computing and assessing sensitivity to model choice. Seasonal analysis of economic time series is used to illustrate ways of approaching such difficulties.

Bayesian methods in hydrology: a review.

David Ríos Insua, Raquel Montes Díez, Jesús Palomo Martínez (2002)

RACSAM

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Hydrology and water resources management are inherently affected by uncertainty in many of their involved processes, including inflows, rainfall, water demand, evaporation, etc. Statistics plays, therefore, an essential role in their study. We review here some recent advances within Bayesian statistics and decision analysis which will have a profound impact in these fields.

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.