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- W1657804153 abstract "AbstractThe entropy is one of the most applicable uncertainty measures in many statistical and en-gineering problems. In statistical literature, the entropy is used in calculation of the Kullback-Leibler (KL) information which is a powerful mean for performing goodness of fit tests. RankedSet Sampling (RSS) seems to provide improved estimators of many parameters of the popu-lation in the huge studied problems in the literature. It is developed for situations where thevariable of interest is difficult or expensive to measure, but where ranking in small sub-samplesis easy. In This paper, we introduced two estimators for the entropy and compare them witheach other and the estimator of the entropy in Simple Random Sampling (SRS) in the senseof bias and Root of Mean Square Errors (RMSE). It is observed that the RSS scheme wouldimprove this estimator. The best estimator of the entropy is used along with the estimator ofthe mean and two biased and unbiased estimators of variance based on RSS scheme, to esti-mate the KL information and perform goodness of fit tests for exponentiality and normality.The desired critical values and powers are calculated. It is also observed that RSS estimatorswould increase powers." @default.
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- W1657804153 date "2011-06-09" @default.
- W1657804153 modified "2023-09-27" @default.
- W1657804153 title "Improved estimator of the entropy and goodness of fit tests in ranked set sampling" @default.
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