Log-logistic parameters estimation using moving extremes ranked set sampling design
In statistical parameter estimation problems, how well the parameters are estimated
largely depends on the sampling design used. In the current paper, a modification of ranked set
sampling (RSS) called moving extremes RSS (MERSS) is considered for the estimation of the
scale and shape parameters for the log-logistic distribution. Several traditional estimators and
ad hoc estimators will be studied under MERSS. The estimators under MERSS are compared
to the corresponding ones under SRS. The simulation results show that the estimators under
MERSS are significantly more efficient than the ones under SRS.
关键词：
moving extremes ranked set sample,
best linear unbiased estimator,
maximum likelihood estimator
