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Showing 2 results for Esmaili
Hamid Esmaili, Mina Towhidi, Seyd Rooalla Roozgar, Mehdi Amiri,
Volume 5, Issue 1 (9-2011)
Abstract
Usually, in testing hypothesis a p_value is used for making decision. Would p_value be the best measure to accept or reject the null hypothesis? Would it be possible to have a better measure than the ordinary p_value? In this paper, hypothesis testing has been considered not as a choice to make decision but as an estimating problem to possible accuracy of a given set, labeled by Θ_0 and p_value would be used as an estimator to possible accuracy of Θ_0 Real numbers as a parametric space has been usually accepted by researcher although the parametric space has been limited in many of applications. A measure named as modified p_value which functions more better than usual p_value in bounded parametric space, would be introduced in normal distribution of one-side and two-side testing.
Masoumeh Esmailizadeh, Ehsan Bahrami Samani,
Volume 13, Issue 2 (2-2020)
Abstract
This paper will analyze inflated bivariate mixed count data. The estimations of model parameters are obtained by the maximum likelihood method. For a bivariate case which has inflation in one or two points, the new bivariate inflated power series distributions are presented. These inflated distributions are used in joint modeling of bivariate count responses. Also, to illustrate the utility of the proposed models, some simulation studies are performed. and finally, a real dataset is analyzed.
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