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Semiparametric Bayesian circular statistics

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  • McVinish, R.
  • Mengersen, K.

Abstract

In areas such as biology, geology and meteorology data often occur as angles. This paper examines the use of Bayesian mixtures of triangular distributions for the semiparametric analysis of circular data. Applications to density estimation, goodness-of-fit testing and semiparametric regression are demonstrated.

Suggested Citation

  • McVinish, R. & Mengersen, K., 2008. "Semiparametric Bayesian circular statistics," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4722-4730, June.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:10:p:4722-4730
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    References listed on IDEAS

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    1. S. P. Brooks & P. Giudici & G. O. Roberts, 2003. "Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 3-39, January.
    2. J. J. Fernández-Durán, 2004. "Circular Distributions Based on Nonnegative Trigonometric Sums," Biometrics, The International Biometric Society, vol. 60(2), pages 499-503, June.
    3. Kaushik Ghosh & Rao Jammalamadaka & Ram Tiwari, 2003. "Semiparametric Bayesian Techniques for Problems in Circular Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(2), pages 145-161.
    4. Ulric Lund, 1999. "Least circular distance regression for directional data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 723-733.
    5. F. Perron & K. Mengersen, 2001. "Bayesian Nonparametric Modeling Using Mixtures of Triangular Distributions," Biometrics, The International Biometric Society, vol. 57(2), pages 518-528, June.
    6. T. D. Downs, 2002. "Circular regression," Biometrika, Biometrika Trust, vol. 89(3), pages 683-698, August.
    7. Sylvia. Richardson & Peter J. Green, 1997. "On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(4), pages 731-792.
    8. Sonia Petrone, 1999. "Random Bernstein Polynomials," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 26(3), pages 373-393, September.
    9. Jones, M.C. & Pewsey, Arthur, 2005. "A Family of Symmetric Distributions on the Circle," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1422-1428, December.
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    Cited by:

    1. Rodríguez, Carlos E. & Núñez-Antonio, Gabriel & Escarela, Gabriel, 2020. "A Bayesian mixture model for clustering circular data," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    2. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.

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