TY - JOUR ID - 13565 TI - Circular Outliers Detection Using a Mixture of Von Mises Distributions JO - Journal of Advanced Mathematical Modeling JA - JAMM LA - en SN - 2251-8088 AU - Golalizadeh, Mousa AU - Abdi, Khadijeh AU - Baghfalaki, Taban AD - University Lecturer / Tarbiat Modares University AD - Tarbiat Modares University AD - Y1 - 2018 PY - 2018 VL - 8 IS - 1 SP - 1 EP - 18 KW - ‎Directional data KW - Outlier points KW - Von Mises distribution KW - Mixture models KW - EM algorithm DO - 10.22055/jamm.2018.20998.1394 N2 - Circular data are typical examples of directional data with a specific regular period‎. ‎Because the presence of outliers leads to invalid statistical inferences on the parameters of the circular regression models‎, ‎their prevalence in analyzing these models requires particular attentions‎. ‎There are different approaches for modeling the structure of the data set with outliers in which using the mixture models is among the most important ones‎. ‎As a new idea‎, ‎to study the methods in determining the outlier data and to employ the mixture model of Von Mises distribution are considered in this paper‎. ‎The EM algorithm is utilized to estimate the parameters of these models‎. ‎The performance of the proposed models is investigated using some simulation studies, and then the confusion matrix is considered to evaluate the accuracy of fitting models. ‎Also‎, ‎the proposed methods are applied to analyze a real data set‎, ‎related to the wave directional analysis in the Bushehr province in Iran. UR - https://jamm.scu.ac.ir/article_13565.html L1 - https://jamm.scu.ac.ir/article_13565_a459522918b3badbca0ee261ab17f287.pdf ER -