A GENERALIZATION OF SUJATHA DISTRIBUTION AND ITS APPLICATIONS WITH REAL LIFETIME DATA

Authors

  • Rama Shanker Department of Statistics, Eritrea Institute of Technology, Asmara
  • Kamlesh Kumar Shukla Department of Statistics, Eritrea Institute of Technology, Asmara
  • Hagos Fesshaye Department of Economics, College of Business and Economics, Halhale

DOI:

https://doi.org/10.3126/jist.v22i1.17742

Keywords:

Lindley distribution, Hazard rate function, Mean residual life function, Bonferroni and Lorenz curves, Stress-strength reliability

Abstract

A two-parameter generalization of Sujatha distribution (AGSD), which includes Lindley distribution and Sujatha distribution as particular cases, has been proposed. It's important mathematical and statistical properties including its shape for varying values of parameters, moments, coefficient of variation, skewness, kurtosis, index of dispersion, hazard rate function, mean residual life function, stochastic ordering, mean deviations, Bonferroni and Lorenz curves, and stress-strength reliability have been discussed. Maximum likelihood estimation method has been discussed for estimating its parameters. AGSD provides better fit than Sujatha, Aradhana, Lindley and exponential distributions for modeling real lifetime data.

Journal of Institute of Science and Technology
Volume 22, Issue 1, July 2017, Page: 66-83

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Published

2017-07-18

How to Cite

Shanker, R., Shukla, K. K., & Fesshaye, H. (2017). A GENERALIZATION OF SUJATHA DISTRIBUTION AND ITS APPLICATIONS WITH REAL LIFETIME DATA. Journal of Institute of Science and Technology, 22(1), 66–83. https://doi.org/10.3126/jist.v22i1.17742

Issue

Vol. 22 No. 1 (2017)

Section

Research Articles

License

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