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Showing 2 results for Towhidi
Abbas Mahdavi, Mina Towhidi,
Volume 3, Issue 2 (3-2010)
Abstract
One of the most important issues in inferential statistics is the existence of outlier observations. Since these observations have a great influence on fitted model and its related inferences, it is necessary to find a method for specifying the effect of outlier observations. The aim of this article is to investigate the effect of outlier observations on kernel density function estimation. In this article we have tried to represent a method for identification of outlier observations and their effect on kernel density function estimation by using forward search method
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.
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