Displaying similar documents to “Regression and time series: Discussion.”

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).

Coherence of models and utilities: Discussion.

James M. Dickey, William H. DuMouchel, José M. Bernardo, Simon French, Joseph B. Kadane, Dennis V. Lindley, Anthony O'Hagan, Adrian F. M. Smith, Thomas W. F. Stroud (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Leonard, Tom, The roles of inductive modelling and coherence in Bayesian statistics and by Novick, Melvin R., Dekeyrel, D.F. and Chuang, D.T., Local and regional coherence utility assessment procedures, both of them part of a round table on Coherence of models and utilities held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

On the number of outliers in data from a linear model.

Peter R. Freeman (1980)

Trabajos de Estadística e Investigación Operativa

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This paper reviews models for the occurrence of outliers in data from the linear model. The Bayesian analyses are all closely similar in form, but differ in the way they treat suspected outliers. The models are compared on Darwin's data and one of them is used on data from a 25 factorial experiment. The question on how many outliers are present involves comparison of models with different number of parameters. A solution using proper priors on all parameters...

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).

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.

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...