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Abstract:
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Suppose G is an arbitrary cumulative distribution function symmetric around zero.Motivated by Mameli [Statistics and Probability Letters, 104, 2015, 75-81], we introduce a family of skew symmetric generalizations of G, referred to as Kumaraswamy skew G distributions. We derive mathematical properties and estimation issues for the family. The family is capable of producing better fits than all skew symmetric generalizations of the G distribution, as shown by applications to nine real data sets.
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