Modified ratio estimators using stratified ranked set sampling

Stratified Ranked Set Sampling (SRSS) combines the advantages ofstratification and Ranked set sampling (RSS) to obtain an unbiasedestimator for the population mean, with potentially significant gainsin efficiency. The present paper deals with modified ratio estimatorsof finite population mean using information on coefficient of variationand co-efficient of kurtosis of auxiliary variable in Stratified RankedSet Sampling. It has been shown that these methods are highly beneficial to the estimation based on Stratified Simple Random Sampling(SSRS). The bias and mean squared error of the proposed estimatorswith large sample approximation are derived. Theoretically, it is shownthat these suggested estimators are asymptotically more efficient thanthe estimators in stratified simple random sampling. The results havebeen illustrated by numerical example.