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Agu-Eghwerido distribution, regression model and applications

Author

Listed:
  • Agu Friday Ikechukwu

    (Department of Statistics, University of Calabar, Calabar, Nigeria)

  • Eghwerido Joseph Thomas

    (Department of Statistics, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria .)

Abstract

Modelling lifetime data with simple mathematical representations and an ease in obtaining the parameter estimate of survival models are crucial quests pursued by survival researchers. In this paper, we derived and introduced a one-parameter distribution called the Agu-Eghwerido (AGUE) distribution with its simple mathematical representation. The regression model of the AGUE distribution was also presented. Several basic properties of the new distribution, such as reliability measures, mean residual function, median, moment generating function, skewness, kurtosis, coefficient of variation, and index of dispersion, were derived. The estimation of the proposed distribution parameter was based on the maximum likelihood estimation method. The real-life applications of the distribution were illustrated using two real lifetime negatively and positively skewed data sets. The new distribution provides a better fit than the Pranav, exponential, and Lindley distributions for the data sets. The simulation results showed that the increase in parameter values decreases the mean squared error value. Similarly, the mean estimate tends towards the true parameter value as the sample sizes increase.

Suggested Citation

  • Agu Friday Ikechukwu & Eghwerido Joseph Thomas, 2021. "Agu-Eghwerido distribution, regression model and applications," Statistics in Transition New Series, Statistics Poland, vol. 22(4), pages 59-76, December.
  • Handle: RePEc:vrs:stintr:v:22:y:2021:i:4:p:59-76:n:5
    DOI: 10.21307/stattrans-2021-038
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    References listed on IDEAS

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    1. Ghitany, M.E. & Al-Mutairi, D.K. & Balakrishnan, N. & Al-Enezi, L.J., 2013. "Power Lindley distribution and associated inference," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 20-33.
    2. Vikas Kumar Sharma & Sanjay Kumar Singh & Umesh Singh & Faton Merovci, 2016. "The generalized inverse Lindley distribution: A new inverse statistical model for the study of upside-down bathtub data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(19), pages 5709-5729, October.
    3. Felix Famoye, 2019. "Bivariate exponentiated‐exponential geometric regression model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 73(3), pages 434-450, August.
    4. Rama Shanker, 2016. "Sujatha Distribution And Its Applications," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 391-410, September.
    5. David Hanagal, 2006. "Bivariate Weibull regression model based on censored samples," Statistical Papers, Springer, vol. 47(1), pages 137-147, January.
    6. R. Shanker, 2016. "Sujatha Distribution and its Applications," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(3), pages 391-410, September.
    7. Daniele Cristina Tita Granzotto & Francisco Louzada, 2015. "The Transmuted Log-Logistic Distribution: Modeling, Inference, and an Application to a Polled Tabapua Race Time up to First Calving Data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(16), pages 3387-3402, August.
    8. Ghitany, M.E. & Atieh, B. & Nadarajah, S., 2008. "Lindley distribution and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(4), pages 493-506.
    9. Felix Famoye & Carl Lee, 2017. "Exponentiated-exponential geometric regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(16), pages 2963-2977, December.
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