Alternative Ratio Estimator of Population Mean in Simple Random Sampling

A New Exponential Type Estimator for the Population Mean in Simple Random Sampling

‎In this paper‎, ‎a new estimate of exponential type of auxiliary information to help simple random sampling without replacement of the finite population mean is introduced‎. ‎This new estimator with a few other estimates using two real data sets are compared with the mean square error‎.

Efficient Exponential Ratio Estimator for Estimating the Population Mean in Simple Random Sampling

This paper proposes, with justification, two exponential ratio estimators of population mean in simple random sampling without replacement. Their biases and mean squared error are derived and compared with existing related ratio estimators. Analytical and numerical results show that at optimal conditions, the proposed ratio estimators are always more efficient than the regression estimator and ...

Horvitz-Thompson estimator of population mean under inverse sampling designs

Inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. In this paper, we derive the Horvitz-Thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. We then introduce an alternative unbiased estimator, corresponding to post-st...

Improvement in Estimating The Population Mean Using Dual To Ratio-Cum-Product Estimator in Simple Random Sampling

A New Difference-Cum-Exponential Type Estimator of Finite Population Mean in Simple Random Sampling

Auxiliary information is frequently used to improve the accuracy of the estimators when estimating the unknown population parameters. In this paper, we propose a new difference-cum-exponential type estimator for the finite population mean using auxiliary information in simple random sampling. The expressions for the bias and mean squared error of the proposed estimator are obtained under first ...