Aims/Objectives: We propose a dual method of Carroll's generalized canonical correlation analysis and we prove by means of the proposed criterion that the duality is formulated by exchanging the operators. It is an extension of Carroll's generalized canonical correlation analysis. The approach of analysis is illustrated on the basis of case study.
In this paper, we introduce an extension of the Katz distribution constructed by the beta transformation. This is a new three-parameter distribution for the analysis and modeling of count data, which we call the new extended Katz distribution. We will study the new distribution from a probabilistic and statistical point of view. We perform a comparison study with an other extension of the Katz distribution with two methods: graphical and goodness-of-fit comparisons. For goodness-of-fit, we have considered the real data and the parameters are estimated by the maximum likelihood method.
In this paper, we will construct the bivariate extended Poisson distribution whichgeneralizes the univariate extended Poisson distribution. This law will be obtained by the method of the product of its marginal laws by a factor. This method was demonstrated in [7]. Thus we call the bivariate extended Poisson distribution of type 1 the bivariate extended Poisson distribution obtained by the method of the product of its marginal distributions by a factor. We will show that this distribution belongs to the family of bivariate Poisson distributions and and will highlight the conditions relating to the independence of the marginal variables. A simulation study was realised.
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