On Flexibility of Inverse Lomax-Lindley distribution

Authors

  • J.Y. Falgore Ahmadu Bello University, Zaria, Kaduna State, Nigeria
  • M. Sirajo Ahmadu Bello University, Zaria, Kaduna State, Nigeria
  • A. A. Umar Ahmadu Bello University, Zaria, Kaduna State, Nigeria
  • M. A. Aliyu Ahmadu Bello University, Zaria, Kaduna State, Nigeria

Keywords:

Entropy Inverse, Lomax-Lindley distribution, Inverse Lomax, Rayleigh Monte Carlo, Simulation Inverse, Lomax Inverse, Lomax-G Family

Abstract

Communication in Physical Sciences, 2021, 7(4): 398-410

Authors: J.Y. Falgore*, M. Sirajo, A. A. Umar, M. A. Aliyu

Received:07 September 2021/Accepted 30 November 2021

In this work, a new extension of the Inverse Lomax family of distribution called Inverse Lomax Lindley (IL-L) distribution is proposed. Different properties of the new distribution are derived including moments, moment generating function, Renyi entropy, Shanon entropy, and order statistics. The performances of the maximum likelihood estimates of the parameters of the Inverse Lomax-Lindley distribution were evaluated through a simulation study. Application of the IL-L distribution to two real-life data sets has proved its flexibility.

Downloads

Download data is not yet available.

Author Biographies

J.Y. Falgore, Ahmadu Bello University, Zaria, Kaduna State, Nigeria

Department of Statistics

M. Sirajo, Ahmadu Bello University, Zaria, Kaduna State, Nigeria

Department of Statistics

A. A. Umar, Ahmadu Bello University, Zaria, Kaduna State, Nigeria

Department of Statistics

M. A. Aliyu, Ahmadu Bello University, Zaria, Kaduna State, Nigeria

Department of Statistics

References

Abd El-Monsef, M. M. E. (2016). A new Lindley distribution with location parameter. Communications in Statistics-Theory and Methods, 45, 17, pp. 5204-5219.

Afify, A. Z., Nassar, M., Cordeiro, G. M., & Kumar, D. (2020). The Weibull Marshall–Olkin Lindley distribution: properties and estimation. Journal of Taibah University for Science, 14, 1, pp. 192-204.

Al-khazaleh, M., Al-Omari, A. I., & Al-khazaleh, A. M. (2016). Transmuted two-parameter Lindley distribution. Journal of Statistics Applications and Probability, 5, 3, pp. 1-11.

Alzaatreh, A., Lee, C., & Famoye, F. (2013). A new method for generating families of continuous distributions. Metron, 71, 1, pp. 63-79.

Aryuyuen, S. (2018). Truncated two-parameter Lindley distribution and its application. The Journal of Applied Science, 17, 1, pp. 19-32.

Asgharzadeh, A., Bakouch, H. S., Nadarajah, S., & Sharafi, F. (2016). A new weighted Lindley distribution with application. Brazilian Journal of Probability and Statistics, 30, 1, pp. 1-27.

Asgharzadeh, A. K. B. A. R., Nadarajah, S., & Sharafi, F. (2018). Weibull lindley distribution. Revstat, 16, 1, pp. 87-113.

Bakouch, H. S., Al-Zahrani, B. M., Al-Shomrani, A. A., Marchi, V. A., & Louzada, F. (2012). An extended Lindley distribution. Journal of the Korean Statistical Society, 41, 1, pp. 75-85.

Barco, K. V. P., Mazucheli, J., & Janeiro, V. (2017). The inverse power Lindley distribution. Communications in Statistics-Simulation and Computation, 46, 8, pp.6308-6323.

Elbatal, I., & Elgarhy, M. (2013). Transmuted quasi Lindley distribution: a generalization of the quasi Lindley distribution. International Journal of Pure and Applied Sciences and Technology, 18, 2, pp. 59-70.

Falgore, J.Y. & Doguwa, S.I. (2020). Inverse Lomax G Family of Distributions with applications to Breaking Strength Data. Asian Journal of Probability and Statistics, 8, 2, pp. 49-60.

Falgore, J. Y., Isah, M. N., & Abdulsalam, H. A. (2021). Inverse Lomax-Rayleigh distribution with the application. Heliyon, e08383. https://doi.org/10.1016/j.heliyon.2021.e08383.

Falgore, J. Y., Doguwa, S. I., & Isah, A. (2019). The weibull-inverse lomax (WIL) distribution with application on bladder cancer. Biometrics & Biostatistics International Journal, 8, 5, pp. 195-202.

Ghitany, M. E., Alqallaf, F., Al-Mutairi, D. K., & Husain, H. A. (2011). A two-parameter weighted Lindley distribution and its applications to survival data. Mathematics and Computers in simulation, 81, 6, pp. 1190-1201.

Ghitany, M., Al-Mutairi, D. K. & Nadarajah, S. (2008). Zero-truncated Poisson–lindley distribution and its application. Mathematics and Computers in Simulation, 79, 3, pp. 279-287.

Ghitany, M. E., Al-Mutairi, D. K., Al-Awadhi, F. A., & Al-Burais, M. M. (2012). Marshall-Olkin extended Lindley distribution and its application. International Journal of Applied Mathematics, 25, 5, pp. 709-721.

Ghitany, M. E., Al-Mutairi, D. K., Balakrishnan, N., & Al-Enezi, L. J. (2013). Power Lindley distribution and associated inference. Computational Statistics & Data Analysis, 64, pp. 20-33.

Hassan, A. S., Elgarhy, M., Mohamd, R. E., & Alrajhi, S. (2019). On the alpha power transformed power Lindley distribution. Journal of Probability and Statistics, pp. 1-13. https://doi.org/10.1155/2019/8024769.

Kharazmi, O., Zargar, M., & Ajami, M. (2020). On the Generalized Odd Transmuted Two-Sided Class of Distributions. Statistica, 80, 4, pp. 439-467.

Mahmoudi, E., & Zakerzadeh, H. (2010). Generalized Poisson–lindley distribution. Communications in Statistics—Theory and Methods, 39, 10, pp. 1785-1798.

Merovci, F. (2013). Transmuted lindley distribution. Int. J. Open Problems Compt. Math, 6, 2, pp. 63-72.

Nadarajah, S., Bakouch, H. S., & Tahmasbi, R. (2011). A generalized Lindley distribution. Sankhya B, 73, 2, pp. 331-359.

Nedjar, S., & Zeghdoudi, H. (2016). On gamma Lindley distribution: Properties and simulations. Journal of Computational and Applied Mathematics, 298, pp. 167-174.

Shanker, R., & Mishra, A. (2013). A quasi Lindley distribution. African Journal of Mathematics and Computer Science Research, 6, 4, pp. 64-71.

Zakerzadeh, H., & Dolati, A. (2009). Generalized lindley distribution. Journal of Mathematical Extension, 2009, 3, 2, pp. 13-25.

Zamani, H., & Ismail, N. (2010). Negative binomial-Lindley distribution and its application. Journal of Mathematics and Statistics, 6, 1, pp. 4-9.

Downloads

Published

2021-11-25