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Abstract
We consider nonparametric interval estimation for the population quantiles based on unbalanced ranked set samples. We derived the large sample distribution of the empirical log likelihood ratio statistic for the quantiles. Approximate intervals for quantiles are obtained by inverting the likelihood ratio statistic. The performance of the empirical likelihood interval is investigated and compared with the performance of the intervals based on the ranked set sample order statistics.
Mathematics Subject Classification:
Acknowledgment
The author would like to thank the referees for their comments and suggestions that improved the article.
Notes
L: Lower Error Rate, U: Upper Error Rates, T: Total Error Rate, W: Expected width of the interval, RW: Relative width of EL interval to OS interval, OS: Interval Based on Order Statistics EL: Empirical Likelihood Based Interval.
L: Lower Error Rate, U: Upper Error Rates, T: Total Error Rate, W: Expected width of the interval, RW: Relative width of EL interval to OS interval, OS: Interval Based on Order Statistics EL: Empirical Likelihood Based Interval.
L: Lower Error Rate, U: Upper Error Rates, T: Total Error Rate, W: Expected width of the interval, RW: Relative width of EL interval to OS interval, OS: Interval Based on Order Statistics EL: Empirical Likelihood Based Interval.
L: Lower Error Rate, U: Upper Error Rates, T: Total Error Rate, W: Expected width of the interval, RW: Relative width of EL interval to OS interval, OS: Interval Based on Order Statistics EL: Empirical Likelihood Based Interval.