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An intuitive clustering algorithm for spherical data with application to extrasolar planets

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  • Wen-Liang Hung
  • Shou-Jen Chang-Chien
  • Miin-Shen Yang

Abstract

This paper proposes an intuitive clustering algorithm capable of automatically self-organizing data groups based on the original data structure. Comparisons between the propopsed algorithm and EM [1] and spherical k -means [7] algorithms are given. These numerical results show the effectiveness of the proposed algorithm, using the correct classification rate and the adjusted Rand index as evaluation criteria [5,6]. In 1995, Mayor and Queloz announced the detection of the first extrasolar planet (exoplanet) around a Sun-like star. Since then, observational efforts of astronomers have led to the detection of more than 1000 exoplanets. These discoveries may provide important information for understanding the formation and evolution of planetary systems. The proposed clustering algorithm is therefore used to study the data gathered on exoplanets. Two main implications are also suggested: (1) there are three major clusters, which correspond to the exoplanets in the regimes of disc, ongoing tidal and tidal interactions, respectively, and (2) the stellar metallicity does not play a key role in exoplanet migration.

Suggested Citation

  • Wen-Liang Hung & Shou-Jen Chang-Chien & Miin-Shen Yang, 2015. "An intuitive clustering algorithm for spherical data with application to extrasolar planets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2220-2232, October.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:10:p:2220-2232
    DOI: 10.1080/02664763.2015.1023271
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    Cited by:

    1. 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.
    2. Wen-Liang Hung & Shou-Jen Chang-Chien, 2017. "Learning-based EM algorithm for normal-inverse Gaussian mixture model with application to extrasolar planets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(6), pages 978-999, April.

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