Adebisi A. Ogunde https://orcid.org/0000-0001-8708-8612 , Emmanuel F. Nymphas

© Adebisi A. Ogunde, Emmanuel F. Nymphas. Article available under the CC BY-SA 4.0 licence

ARTICLE

(English) PDF

ABSTRACT

In this paper, we propose a new, four-parameter distribution with increasing, decreasing, bathtub-shaped and a unimodal failure rate, called the Inverse Power Lomax Poisson (IPLP) distribution. The new distribution combines Inverse Power Lomax (IPL) and Poisson distributions. We derive several properties of the new distribution: its probability density function, its reliability and failure rate functions, the quantiles, the stress-strength parameter, complete and incomplete moments, the moment generating function, the probability weighted moment, R?nyi and q-entropies, and order statistics. The study presents the estimation of the model’s parameters based on the maximum likelihood method. The applications of the new distribution are presented using two real data sets, showing its flexibility and potential in modelling lifetime data.

KEYWORDS

probability weighted moments, incomplete moments, quantile function, Renyi entropy.

REFERENCES

Abd-Elfattah, A. M, Hassan, A. S. and Hussein, A. M., (2013). On the Lomax-Poisson Distribution. Proceeding of the 48th The Annual Conference On Statistics, Computer Sciences & Operations Research, Institute of Statistical Studies Research. Cairo University, pp. 25–39.

Abdul-Moniem, I. B., Abdel-Hameed, H. F., (2012). A lifetime distribution with decreasing failure rate. International Journal of Mathematical Education, 33(5), pp. 1–7.

Al-Marzouki, S., Jamal, F., Chesneau, C. and Elgarhy, M., (2020). Type II Topp Leone Power Lomax Distribution with Applications. Mathematics 2020, 8, 4, doi: 10.3390/math8010004.

Al Sobhi, M. M., (2022). The extended Weibull distribution with its properties, estimation and modeling skewed data. Journal of King Saud University – Science, 34(2), pp. 1–15.

Al-Zahrani, B., (2015). An extended Poisson-Lomax distribution. Advances in Mathematics: Scientific Journal, 4(2), pp. 79–89.

Al-Zahrani, B., Sagor, H., (2014). Statistical analysis of the Lomax-Logarithmic distribution. Journal of Statistical Computation and Simulation, 85, pp. 1883–1901.

Cordeiro, G. M., Ortega. E. and Popović, B., (2013). The gamma-Lomax distribution. Journal of Statistical Computation and Simulation, 85(2), pp. 305–319.

Haq, M. A., Hamedani, G. G., Elgarhy, M. and Ramos, P. L., (2020). Marshall–Olkin power Lomax Distribution: Properties and estimation based on complete and censored samples. Int. J. Stat. Probab., 9(1), p. 48.

Hassan, A. S.; Abd-Allah, M., (2019). On the Inverse Power Lomax Distribution. Ann. Data Sci., 6, pp. 259–278, doi:10.1007/s40745-018-0183-y.

Hassan, A. S., Nassr, S. G., (2018). Power Lomax Poisson distribution: Properties and Estimation. Journal of Data Science, 18, pp. 105–128.

Lemonte, A. J., Cordeiro G. M., (2013). An extended Lomax distribution. Statistics, 47(4), pp. 800–816.

Nagarjuma, V. B. V., Vardhan, R. V. and Chesnau, C., (2022). Nadarajah Haghighi- Lomax distribution and is Applications. Math. Comput. Appl., 27 (30), pp. 1–13.

Ramos, M. W. A., Marinho, P. R. D., da Silva R. V. and Cordeiro, G. M., (2013). The exponentiated Lomax Poisson distribution with an application to lifetime data. Advances and Applications in Statistics, 34(2), pp. 107–135.

Roman, M., Louzada, F., Cancho, V. G. and Leite, J. G., (2012). A new long-term survival distribution for cancer data. Journal of Data Science, 10(2), pp. 241–258.

Simth, R. L., Naylor, J. C., (1987). A comparison of maximum likelihood and Bayesian estimators for three-parameter Weibull distribution. Applied Statistics, 36, pp. 358– 369.

Tahir, M. H., Cordeiro, G. M., Mansoor, M. and Zubair, M., (2015). The Weibull- Lomax distribution: Properties and applications. Hacettepe Journal of Mathematics and Statistics, 44(2), pp. 461–480.

Tahir, M. H., Hussain, M. A., Cordeiro, G. M., Hamedani, G. G., Mansoor, M. and Zubair, M., (2016). The Gumbel-Lomax distribution: Properties and applications. Journal of Statistical Theory and Applications, 15(1), pp. 61–79.

Back to top
© 2019–2025 Copyright by Statistics Poland, some rights reserved. Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0) Creative Commons — Attribution-ShareAlike 4.0 International — CC BY-SA 4.0