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A new generalization of generalized half-normal distribution: properties and regression models

Author

Listed:
  • Emrah Altun

    (Bartin University)

  • Haitham M. Yousof

    (Benha University)

  • G.G. Hamedani

    (Marquette University)

Abstract

In this paper, a new extension of the generalized half-normal distribution is introduced and studied. We assess the performance of the maximum likelihood estimators of the parameters of the new distribution via simulation study. The flexibility of the new model is illustrated by means of four real data sets. A new log-location regression model based on the new distribution is also introduced and studied. It is shown that the new log-location regression model can be useful in the analysis of survival data and provides more realistic fits than other competitive regression models.

Suggested Citation

  • Emrah Altun & Haitham M. Yousof & G.G. Hamedani, 2018. "A new generalization of generalized half-normal distribution: properties and regression models," Journal of Statistical Distributions and Applications, Springer, vol. 5(1), pages 1-16, December.
    • Handle: RePEc:spr:jstada:v:5:y:2018:i:1:d:10.1186_s40488-018-0089-4
    DOI: 10.1186/s40488-018-0089-4
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    References listed on IDEAS

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    1. Rodrigo R. Pescim & Edwin M. M. Ortega & Gauss M. Cordeiro & Morad Alizadeh, 2017. "A new log-location regression model: estimation, influence diagnostics and residual analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 233-252, January.
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