Displaying similar documents to “Graphical models for hierarchical computations in the analysis and design of replications.”

The Bayesian approach to the combination of forecasts: some extensions into a skewed environment.

Gerrit K. Janssens (1987)

Trabajos de Estadística

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Where a decision-maker has to rely on expert opinions a need for a normative model to combine these forecasts appears. This can be done using Bayes' formula and by making some assumptions on the prior distribution and the distribution of the expert assessments. We extend the case to skewed distributions of these assessments. By using an Edgeworth expansion of the density function including the skewness parameter, we are able to obtain the formula to combine the forecasts in a Bayesian...

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.

Probability of reversal in an election with more than two candidates.

Vijay K. Rohatgi (1982)

Trabajos de Estadística e Investigación Operativa

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Consider an election with three candidates A, A and A. Suppose that N is the total number of votes cast of which A receives a votes, A receives a votes and A receives a = N - (a + a) votes. We assume without loss of generality that a > a > a. Suppose further that n votes are irregular or suspect. If these votes are removed it is possible that the result of the election may be reversed. Does such a possibility preclude the determination of the rightful winner without holding...

A note on the likelihood and moments of the skew-normal distribution.

Eliseo Martínez, Héctor Varela, Héctor W. Gómez, Heleno Bolfarine (2008)

SORT

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In this paper an alternative approach to the one in Henze (1986) is proposed for deriving the odd moments of the skew-normal distribution considered in Azzalini (1985). The approach is based on a Pascal type triangle, which seems to greatly simplify moments computation. Moreover, it is shown that the likelihood equation for estimating the asymmetry parameter in such model is generated as orthogonal functions to the sample vector. As a consequence, conditions for a unique solution of...

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...

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,...

A note on interval estimation for the mean of inverse Gaussian distribution.

M. Arefi, G. R. Mohtashami Borzadaran, Y. Vaghei (2008)

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In this paper, we study the interval estimation for the mean from inverse Gaussian distribution. This distribution is a member of the natural exponential families with cubic variance function. Also, we simulate the coverage probabilities for the confidence intervals considered. The results show that the likelihood ratio interval is the best interval and Wald interval has the poorest performance.