جستجوی مقالات مرتبط با کلیدواژه "تقارن بیضوی" در نشریات گروه "آمار"

‎This paper presents a nonparametric multi-class depth-based classification approach for multivariate data. This approach is easy to implement rather than most existing nonparametric methods that have computational complexity. If the assumption of the elliptical symmetry holds, this method is equivalent to the Bayes optimal rule. Some simulated data sets as well as real example have been used to evaluate the performance of these depth-based classifiers.

This paper is concerned about the concept os asymmetry. The different types of asymmetry for univariate and multivariate distributions have introduces been considered as well as some of usual asymmetry criteria. A brief overview of method for adding the capability of modeling asymmetry to a symmetry distribution is also a secondary purpose of this paper.