Open AccessEstimation of the Exponential Pareto Distribution’s Parameters under Ranked and Double Ranked Set Sampling Designs
Author(s) -
M. Sabry,
Ehab M. Almetwally
Publication year - 2021
Publication title -
pakistan journal of statistics and operation research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.354
H-Index - 15
eISSN - 2220-5810
pISSN - 1816-2711
DOI - 10.18187/pjsor.v17i1.3448
Subject(s) - mathematics , statistics , estimator , weibull distribution , pareto distribution , exponential distribution , efficiency , monte carlo method , exponential function , simple random sample , sampling design , population , mathematical analysis , demography , sociology
In this paper, the derivation of the likelihood function for parameter estimation based on double ranked set sampling (DRSS) designs used by Sabry el.al.; (2019) for the estimation of the parameters of the power generalized Weibull distribution is considered. The developed likelihood function is then used for the estimation of the exponential Pareto distribution parameters. The maximum likelihood estimators (MLEs) are then investigated and compared to the corresponding ones based on simple random sampling (SRS) and ranked set sampling (RSS) designs. A Monte Carlo simulation is conducted and the absolute relative biases, mean square errors, and efficiencies are compared for the different designs. The relative efficiency of the DRSS estimates with respect to other designs was found to be higher in case of the exponential Pareto distribution (EP).