Displaying similar documents to “Bayesian stopping rule in discrete parameter space with multiple local maxima”

Some history of the hierarchical Bayesian methodology.

Irving John Good (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

A standard tecnique in subjective Bayesian methodology is for a subject (you) to make judgements of the probabilities that a physical probability lies in various intervals. In the Bayesian hierarchical technique you make probability judgements (of a higher type, order, level or stage) concerning the judgements of lower type. The paper will outline some of the history of this hierarchical technique with emphasis on the contributions by I. J. Good because I have read every word written...

On not being rational.

I. Richard Savage (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

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? ...

Likelihood and the Bayes procedure.

Hirotugu Akaike (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

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.

Foundations of subjective probability and decision making: Discussion.

Irving John Good, Ludovico Piccinato, Cesáreo Villegas, James M. Dickey, Morris H. DeGroot, Donald A. S. Fraser, Simon French, Dennis V. Lindley (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

Discussion on the papers by Girón, F. J. and Ríos, S., Quasi-Bayesian behaviour: a more realistic approach to dicision making? and by Hill, B. M., On finite additivity, non-conglomerability and statistical paradoxes, both of them part of a round table on Foundations of Subjective Probability and Decision Making 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

Similarity:

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).

Bayesian reference analysis for proportional hazards model of random censorship with Weibull distribution

Maria Ajmal, Muhammad Yameen Danish, Ayesha Tahira (2022)

Kybernetika

Similarity:

This article deals with the objective Bayesian analysis of random censorship model with informative censoring using Weibull distribution. The objective Bayesian analysis has a long history from Bayes and Laplace through Jeffreys and is reaching the level of sophistication gradually. The reference prior method of Bernardo is a nice attempt in this direction. The reference prior method is based on the Kullback-Leibler divergence between the prior and the corresponding posterior distribution...

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

Similarity:

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).

Nonparametric estimation: the survival function.

Alfonso García Pérez (1984)

Trabajos de Estadística e Investigación Operativa

Similarity:

The unknown survival function S(t) of a random variable T ≥ 0 is considered. First we study the properties of S(t) and then, we estimate it from a Bayesian point of view. We compare the estimator with the posterior mean and we finish giving Bayes rules for linear functions of S(t).

The roles of inductive modelling and coherence in Bayesian statistics.

Tom Leonard (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

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...

Estimation of random survival functions: a linear approach.

Vicente Quesada Paloma, Alfonso García Pérez (1982)

Qüestiió

Similarity:

In the first part of this work, a Survival function is considered which is supposed to be an Exponential Gamma Process. The main statistical and probability properties of this process and its Bayesian interpretation are considered. In the second part, the problem to estimate, from a Bayesian view point, the Survival function is considered, looking for the Bayes rule inside of the set of linear combinations of a given set of sample functions. We finish with an...

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

Peter R. Freeman (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

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...