Displaying similar documents to “MLE for the γ-order Generalized Normal Distribution”

Construction of multivariate distributions: a review of some recent results.

José María Sarabia, Emilio Gómez-Déniz (2008)

SORT

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The construction of multivariate distributions is an active field of research in theoretical and applied statistics. In this paper some recent developments in this field are reviewed. Specifically, we study and review the following set of methods: (a) Construction of multivariate distributions based on order statistics, (b) Methods based on mixtures, (c) Conditionally specified distributions, (d) Multivariate skew distributions, (e) Distributions based on the method of the variables...

Compound geometric and Poisson models

Nooshin Hakamipour, Sadegh Rezaei, Saralees Nadarajah (2015)

Kybernetika

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Many lifetime distributions are motivated only by mathematical interest. Here, eight new families of distributions are introduced. These distributions are motivated as models for the stress of a system consisting of components working in parallel/series and each component has a fixed number of sub-components working in parallel/series. Mathematical properties and estimation procedures are derived for one of the families of distributions. A real data application shows superior performance...

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...

Test for Independence of the Variables with Missing Elements in One and the Same Column of the Empirical Correlation Matrix

Veleva, Evelina (2008)

Serdica Mathematical Journal

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2000 Mathematics Subject Classification: 62H15, 62H12. We consider variables with joint multivariate normal distribution and suppose that the sample correlation matrix has missing elements, located in one and the same column. Under these assumptions we derive the maximum likelihood ratio test for independence of the variables. We obtain also the maximum likelihood estimations for the missing values.