Displaying similar documents to “On the selection of the parameters of an exponential gamma process prior in Bayesian nonparametric estimation.”

Nonparametric estimation: the survival function.

Alfonso García Pérez (1984)

Trabajos de Estadística e Investigación Operativa

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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).

Estimation of random survival functions: a linear approach.

Vicente Quesada Paloma, Alfonso García Pérez (1982)

Qüestiió

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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...

Pivotal inference and the Bayesian controversy.

George A. Barnard (1980)

Trabajos de Estadística e Investigación Operativa

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The theory of pivotal inference applies when parameters are defined by reference to their effect on observations rather than their effect on distributions. It is shown that pivotal inference embraces both Bayesian and frequentist reasoning.

Objective Bayesian point and region estimation in location-scale models.

José M. Bernardo (2007)

SORT

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Point and region estimation may both be described as specific decision problems. In point estimation, the action space is the set of possible values of the quantity on interest; in region estimation, the action space is the set of its possible credible regions. Foundations dictate that the solution to these decision problems must depend on both the utility function and the prior distribution. Estimators intended for general use should surely be invariant under one-to-one transformations,...

Nonparametric Bayesian estimation and goodness of fit test.

Vicente Quesada Paloma, Alfonso García Pérez (1985)

Qüestiió

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We first make a review of prior distributions neutral to the right, and then we get the Bayes rule for the survival function S(t) = 1 - F(t), with quadratic loss, with these prior distributions. We give, after that, the estimator with a special kind of processes neutral to the right, the homogeneous processes. We get in point four the linear Bayes rule and we give there an interpretation of the parameters. We finish with a Bayesian generalization of the Kolmogorov-Smirnov...

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 survival analysis based on the Rayleigh model.

Samir K. Bhattacharya, K. Tyagi Ravinder (1990)

Trabajos de Estadística

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In this paper, the Bayesian analysis of the survival data arising from a Rayleigh model is carried out under the assumption that the clinical study based on n patients is terminated at the d death, for some preassigned d (0 < d ≤ n), resulting in the survival times t ≤ t ≤ ... ≤ t, and (n - d) survivors. For the prior knowledge about the Rayleigh parameter, the gamma density, the inverted gamma density, and the beta density of the second kind are respectively assumed, and for...

Some history of the hierarchical Bayesian methodology.

Irving John Good (1980)

Trabajos de Estadística e Investigación Operativa

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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...