The generalized von Mises distribution |
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| Institution: | 1. Institute of Mathematical Statistics and Actuarial Science, University of Berne, Sidlerstrasse 5, 3012 Berne, Switzerland;2. Department of Statistics and Applied Probability, University of California, Santa Barbara, CA 93106, USA;1. College of Applied Sciences, Beijing University of Technology, Beijing, 100124, China;2. Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China;1. Department of Mathematics, Bucknell University, Lewisburg, PA 17837, USA;2. Department of Mathematics, Colorado State University, Fort Collins, CO 80523, USA;1. Laboratório de Ecologia e Conservação, Departamento de Biologia Geral, Universidade Federal de Minas Gerais, Avenida Antonio Carlos, no. 6627, Belo Horizonte, MG 31270-901, Brazil;2. Instituto SerraDiCal de Pesquisa e Conservação, Rua José Hemetério de Andrade, no. 570, Belo Horizonte, MG 30493-180, Brazil;3. Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, 80523-1474, USA;4. Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Avenida Bandeirantes, no. 3900, Ribeirão Preto, SP, 14040-901, Brazil;1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, 410082, People’s Republic of China;2. Center for Research on Leading Technology of Special Equipment, School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou, 510006, People’s Republic of China;3. Centre for Innovative Structures and Materials, School of Engineering, RMIT University, Melbourne, 3001, Australia |
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| Abstract: | A generalization of the von Mises distribution, which is broad enough to cover unimodality as well as multimodality, symmetry as well as asymmetry of circular data, is discussed here. We study this distribution in some detail and discuss its many features, some inferential and computational aspects, and provide some important results including characterization properties for this distribution. |
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