A new improved generalized class of estimators for population distribution function using auxiliary variable under simple random sampling

Abstract

This article aims to suggest a new improved generalized class of estimators for finite population distribution function of the study and the auxiliary variables as well as mean of the usual auxiliary variable under simple random sampling. The numerical expressions for the bias and mean squared error (MSE) are derived up to first degree of approximation. From our generalized class of estimators, we obtained two improved estimators. The gain in second proposed estimator is more as compared to first estimator. Three real data sets and a simulation are accompanied to measure the performances of our generalized class of estimators. The MSE of our proposed estimators is minimum and consequently percentage relative efficiency is higher as compared to their existing counterparts. From the numerical outcomes it has been shown that the proposed estimators perform well as compared to all considered estimators in this study.

Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling

“…The biases of and respectively are given in equation [ 16 , 17 ]: and the MSEs of and are given in equation [ 18 , 19 ]: The [9] also proposed a generalized ratio-type mean estimator, given in equation [ 20 ]: …”

“…[ [16] , [17] , [18] ], subsamples of non-respondents were taken using two-phase sampling technique, and developed several mean estimators of a finite population. In case of multi-auxiliary variables [ 19 ], suggested several estimators for population mean estimation. Under the situation of non-response.…”

Enhanced exponential ratio-cum-ratio estimator in ranked set sampling using transformed auxiliary information

“…The [ 19 ] suggested a novel estimator for population mean using idea of rank under stratified random sampling. The [ 20 ] discussed a new family of estimators using rank idea for population distribution function. Some latest works done using rank set sampling see Refs.…”

New generalized class of estimators for estimation of finite population mean based on probability proportional to size sampling using two auxiliary variables: A simulation study

“…Mahdizadeh and Zamanzade 11 proposed an interval estimation of the population mean in ranked set sampling. Ahmad et al 12 recommended a new improved generalized class of estimators for population distribution function using the auxiliary variable under simple random sampling. Muhammad et al 13 suggested an enhanced ratio-type estimator for finite population mean using the auxiliary variable in simple random sampling.…”