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Some Properties and Quantile Regression for the Log-Lindley Distribution

In: Directional and Multivariate Statistics

Author

Listed:
  • Seng Huat Ong

    (UCSI University, Institute of Actuarial Science and Data Analytics
    University of Malaya, Institute of Mathematical Sciences)

  • Choung Min Ng

    (University of Malaya, Institute of Mathematical Sciences)

  • Subrata Chakraborty

    (Dibrugarh University, Department of Statistics)

Abstract

There is much recent interest in distributions alternative to the classical beta distribution. In this paper, financial risk and inequality measures have been derived for the log-Lindley distribution with support on the unit interval and a robust quantile regression is also proposed. The log-Lindley distribution is parameterized in terms of its quantile function to permit the modelling of the covariate effects across the whole distribution of response, instead of restriction to the mean. The performance of the log-Lindley quantile regression is examined by Monte Carlo simulations with application to a risk management data set.

Suggested Citation

  • Seng Huat Ong & Choung Min Ng & Subrata Chakraborty, 2025. "Some Properties and Quantile Regression for the Log-Lindley Distribution," Springer Books, in: Somesh Kumar & Barry C. Arnold & Kunio Shimizu & Arnab Kumar Laha (ed.), Directional and Multivariate Statistics, pages 317-337, Springer.
    • Handle: RePEc:spr:sprchp:978-981-96-2004-3_16
    DOI: 10.1007/978-981-96-2004-3_16
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