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B0445
Title: An extension of sine-skewed circular distributions Authors:  Yoichi Miyata - Takasaki City University of Economics (Japan) [presenting]
Abstract: The sine skewed circular distribution is a tractable circular probability model that can be asymmetric in shape and that has the advantage that the sine and cosine moments can be written in explicit forms. We use the framework of Ley and Verdebout to propose a new family of probability distributions, including the sine skewed circular distribution. This family includes distributions that can give stronger asymmetry than the sine skewed circular distribution. Furthermore, we show that a subfamily of the proposed distributions is identifiable with respect to parameters, and all distributions in the subfamily have explicit sine and cosine moments. We will also discuss an extension of these results to probability models on cylinders if time is allowed.