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Estimation of finite population mean using two auxiliary variables under stratified random sampling

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Yadav R., Tailor R.
Statistics in Transition new series
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2020
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vol. 21
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issue 1
1-12
EN
This paper addresses the problem of an alternative approach to estimating the population mean of the study variable with the help of the auxiliary variable under stratified random sampling. The properties of the suggested estimator have been studied under large sample approximation. It has been demonstrated that the suggested estimator is more efficient than other considered estimators. To judge the merits of the proposed estimator, an empirical study has been carried out to support the present study.
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Ratio estimation of two population means in two-phase stratified random sampling under a scrambled response situation

100%
Das P., Singh G. N., Bandyopadhyay A.
Statistics in Transition new series
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2023
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vol. 24
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issue 5
45-61
EN
In this paper, we have described the development of an effective two-phase stratified random sampling estimation procedure in a scrambled response situation. Two different exponential, regression-type estimators were formed separately for different structures of two-phase stratified sampling schemes. We have studied the properties of the suggested strategy. The performance of the proposed strategy has been demonstrated through numerical evidence based on a data set of a natural population and a population generated through simulation studies. Taking into consideration the encouraging findings, suitable recommendations for survey statisticians are prepared for the application of the proposed strategy in real-life conditions.
3
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Improved Separate Ratio Exponential Estimator for Population Mean Using Auxiliary Information

86%
Yadav R., Upadhyaya L. N., Singh H. P., Chatterjee S.
Statistics in Transition new series
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2011
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vol. 12
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issue 2
401-412
EN
This paper advocates the improved separate ratio exponential estimator for population mean of the study variable y using the information based on auxiliary variable x in stratified random sampling. The bias and mean squared error (MSE) of the suggested estimator have been obtained upto the first degree of approximation. The theoretical and numerical comparisons are carried out to show the efficiency of the suggested estimator over sample mean estimator, usual separate ratio and separate product estimator.
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