Parameter Estimation of Dagum Distribution

Arun Kumar Rao; Himanshu Pandey

doi:https://doi.org/10.14445/22315373/IJMTT-V66I9P527

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 66 | Issue 9 | Year 2020 | Article Id. IJMTT-V66I9P527 | DOI : https://doi.org/10.14445/22315373/IJMTT-V66I9P527

Parameter Estimation of Dagum Distribution

Arun Kumar Rao, Himanshu Pandey

Citation :

Arun Kumar Rao, Himanshu Pandey, "Parameter Estimation of Dagum Distribution," International Journal of Mathematics Trends and Technology (IJMTT), vol. 66, no. 9, pp. 239-245, 2020. Crossref, https://doi.org/10.14445/22315373/IJMTT-V66I9P527

Abstract

Dagum distribution is considered. Bayesian method of estimation is employed in order to estimate the shape parameter of Dagum distribution by using quasi and gamma priors. In this paper, the Bayes estimators of the shape parameter have been obtained under squared error, precautionary and weighted loss functions.

Keywords

- Dagum distribution, Bayesian method, quasi and gamma priors, squared error, precautionary and weighted loss functions.

References

[1] Dagum, C., “A model of income distribution and the conditions of existence of moments of finite order,” Bulletin of the International Statistical Institute, 46 (Proceedings of the 40th Session of the ISI, Warsaw, Contributed Papers), pp. 199-205, 1975.
[2] Naqash Saima, Ahamad, S.P. and Ahamad A., “Bayesian Analysis of Dagum Distribution,” Journal of Reliability and Statistical Studies, Vol. 10, Issue 1, 123-136, 2017.
[3] Zellner, A., “Bayesian estimation and prediction using asymmetric loss functions,” Jour. Amer. Stat. Assoc., 91, 446-451, 1986.
[4] Basu, A. P. and Ebrahimi, N., “Bayesian approach to life testing and reliability estimation using asymmetric loss function,” Jour. Stat. Plann. Infer., 29, 21-31, 1991.
[5] Norstrom, J. G., “The use of precautionary loss functions in Risk Analysis,” IEEE Trans. Reliab., 45(3), 400-403, 1996.
[6] Ahmad, S. P., et al., “Bayesian Estimation for the Class of Life-Time Distributions under Different Loss Functions,” Statistics and Applications, Vol. 14, Nos. 1&2, pp. 75-91, 2016.