Estimating the parameters of Lomax distribution from imprecise information
- Abbas Pak*, email@example.comDepartment of Computer Sciences, Faculty of Mathematical Sciences, Shahrekord University, P. O. Box 115, Shahrekord, Iran.Mohammad Reza Mahmoudimahmoudi.firstname.lastname@example.orgDepartment of Statistics, Fasa University, Fasa, Iran*Corresponding author
- Corresponding Author
- Abbas Pakpak@sci.sku.ac.ir
- https://doi.org/10.2991/jsta.2018.17.1.9How to use a DOI?
- Imprecise data, Fuzzy information, Lomax distribution, Maximum likelihood estimation, Bayesian estimation
Traditional statistical approaches for estimating the parameters of Lomax distribution have dealt with precise information. However, in real world situations, some information about an underlying system might be imprecise and are represented in the form of fuzzy information. In this paper, we consider the problem of estimating the parameters of Lomax distribution when the available observations are described by means of fuzzy information. We obtain the maximum likelihood estimate of the parameters by using the Newton-Raphson as well as the EM algorithm. We also provide an approximation namely, Tierney and Kadane’s approximation, to compute the Bayes estimates of the unknown parameters. The estimation procedures are discussed in details and compared via Monte Carlo simulations in terms of their estimated biases and mean squared errors. Finally, analysis of one data set is provided for the purpose of illustration.
- Copyright © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
Cite this article
TY - JOUR AU - Abbas Pak AU - Mohammad Reza Mahmoudi PY - 2018 DA - 2018/03 TI - Estimating the parameters of Lomax distribution from imprecise information JO - Journal of Statistical Theory and Applications SP - 122 EP - 135 VL - 17 IS - 1 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.2018.17.1.9 DO - https://doi.org/10.2991/jsta.2018.17.1.9 ID - Pak2018 ER -