Displaying similar documents to “Asymptotic covariances for the generalized gamma distribution”

Bounds on tail probabilities for negative binomial distributions

Peter Harremoës (2016)

Kybernetika

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In this paper we derive various bounds on tail probabilities of distributions for which the generated exponential family has a linear or quadratic variance function. The main result is an inequality relating the signed log-likelihood of a negative binomial distribution with the signed log-likelihood of a Gamma distribution. This bound leads to a new bound on the signed log-likelihood of a binomial distribution compared with a Poisson distribution that can be used to prove an intersection...

Approximate Bayesian methods.

Dennis V. Lindley (1980)

Trabajos de Estadística e Investigación Operativa

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This paper develops asymptotic expensions for the ratios of integrals that occur in Bayesian analysis: for example, the posterior mean. The first term omitted is 0(n) and it is shown how the term 0(n) can be of importance.

A multimodal beta distribution with application to economic data

Saralees Nadarajah, Samuel Kotz (2007)

Applicationes Mathematicae

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Beta distributions are popular models for economic data. In this paper, a new multimodal beta distribution with bathtub shaped failure rate function is introduced. Various structural properties of this distribution are derived, including its cdf, moments, mean deviation about the mean, mean deviation about the median, entropy, asymptotic distribution of the extreme order statistics, maximum likelihood estimates and the Fisher information matrix. Finally, an application to consumer price...

Information Matrix for Beta Distributions

Aryal, Gokarna, Nadarajah, Saralees (2004)

Serdica Mathematical Journal

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2000 Mathematics Subject Classification: 33C90, 62E99. The Fisher information matrix for three generalized beta distributions are derived.

The likelihood ratio test for general mixture models with or without structural parameter

Jean-Marc Azaïs, Élisabeth Gassiat, Cécile Mercadier (2009)

ESAIM: Probability and Statistics

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This paper deals with the likelihood ratio test (LRT) for testing hypotheses on the mixing measure in mixture models with or without structural parameter. The main result gives the asymptotic distribution of the LRT statistics under some conditions that are proved to be almost necessary. A detailed solution is given for two testing problems: the test of a single distribution against any mixture, with application to Gaussian, Poisson and binomial distributions; the test of the number...

Testing in locally conic models, and application to mixture models

Didier Dacunha-Castelle, Elisabeth Gassiat (2010)

ESAIM: Probability and Statistics

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In this paper, we address the problem of testing hypotheses using maximum likelihood statistics in non identifiable models. We derive the asymptotic distribution under very general assumptions. The key idea is a local reparameterization, depending on the underlying distribution, which is called locally conic. This method enlights how the general model induces the structure of the limiting distribution in terms of dimensionality of some derivative space. We present various applications...