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Nicola Loperfido, U. di Urbino Print
Friday, 25 September 2009, 14:30 - 15:30

Testing for Normality when the Sampled Distribution is Extended Skew-Normal

Nicola Loperfido, Universita degli Studi di Urbino

Abstract:The extended skew-normal (ESN) class of densities include the normal ones as special cases. Unfortunately, its information matrix is singular under normality, thus preventing application of standard likelihood-based methods for testing the null hypothesis of normality. For univariate ESN distributions the sample skewness provides the locally most powerful test for normality among the location and scale invariant ones. The generalization to multivariate ESN distributions considers projections of the data onto the direction corresponding to maximal skewness. Related computational problems simplifies for the multivariate ESN distribution, where the direction maximizing skewness is shown to have a simple parametric interpretation. Applications of theoretical results deal with height and weight of Australian athletes.

Location: Plaine, Room 2.NO.708
Contact: Jacqueline DOUILLY, This e-mail address is being protected from spam bots, you need JavaScript enabled to view it

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