Transmuted geometric distribution with applications in modelling and regression analysis of count data

• Subrata Chakraborty ^[1] ; Deepesh Bhati ^[2]
  1. [1] Dibrugarh University

     Dibrugarh University

     India

     
  2. [2] Central University of Rajasthan

     Central University of Rajasthan

     India

     
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 40, Nº. 1, 2016, págs. 153-176
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • A two-parameter transmuted geometric distribution is prop osed as a new generalization of the geometric distribution by employing the quadratic transmu tation techniques of Shaw and Buckley.

    The additional parameter plays the role of controlling the t ail length. Distributional properties of the proposed distribution are investigated. Maximum likel ihood estimation method is discussed along with some data fitting experiments to show its advantag es over some existing distributions in literature. The tail flexibility of density of aggregate l oss random variable assuming the proposed distribution as primary distribution is outlined and prese nted along with a illustrative modelling of aggregate claim of a vehicle insurance data. Finally, we pre sent a count regression model based on the proposed distribution and carry out its comparison wi th some established models

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