85,767 research outputs found
On Bivariate Exponentiated Extended Weibull Family of Distributions
In this paper, we introduce a new class of bivariate distributions called the
bivariate exponentiated extended Weibull distributions. The model introduced
here is of Marshall-Olkin type. This new class of bivariate distributions
contains several bivariate lifetime models. Some mathematical properties of the
new class of distributions are studied. We provide the joint and conditional
density functions, the joint cumulative distribution function and the joint
survival function. Special bivariate distributions are investigated in some
detail. The maximum likelihood estimators are obtained using the EM algorithm.
We illustrate the usefulness of the new class by means of application to two
real data sets.Comment: arXiv admin note: text overlap with arXiv:1501.03528 by other author
Bivariate Gamma Distributions for Image Registration and Change Detection
This paper evaluates the potential interest of using bivariate gamma distributions for image registration and change detection. The first part of this paper studies estimators for the parameters of bivariate gamma distributions based on the maximum likelihood principle and the method of moments. The performance of both methods are compared in terms of estimated mean square errors and theoretical asymptotic variances. The mutual information is a classical similarity measure which can be used for image registration or change detection. The second part of the paper studies some properties of the mutual information for bivariate Gamma distributions. Image registration and change detection techniques based on bivariate gamma distributions are finally investigated. Simulation results conducted on synthetic and real data are very encouraging. Bivariate gamma distributions are good candidates allowing us to develop new image registration algorithms and new change detectors
Bivariate extreme value distributions
In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given
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