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A General Family of Estimators for Estimating Population Variance Using Known Value of Some Population Parameter(s)
A general family of estimators for estimating the population variance of the variable under study, which make use of known value of certain population parameter(s), is proposed. Some well known estimators have been shown as particular member of this family.
A GENERAL FAMILY OF ESTIMATORS FOR ESTIMATING POPULATION MEAN USING KNOWN VALUE OF SOME POPULATION PARAMETER(S)
A general family of estimators for estimating the population mean of the variable under study, which make use of known value of certain population parameter(s), is proposed. Under Simple Random Sampling Without Replacement (SRSWOR) scheme, the expressions of bias and mean squared error (MSE) up to first order of approximation are derived. Some well known estimators have been shown as particular member of this family.
Almost Unbiased Exponential Estimator for the Finite Population Mean
In this paper we have proposed an almost unbiased ratio and product type exponential estimator for the finite population mean Y. It has been shown that Bahl and Tuteja (1991) ratio and product type exponential estimators are particular members of the proposed estimator. Empirical study is carried to demonstrate the superiority of the proposed estimator.
Almost Unbiased Ratio and Product Type Estimator of Finite Population Variance Using the Knowledge of Kurtosis of an Auxiliary Variable in Sample Surveys
It is well recognized that the use of auxiliary information in sample survey design results in efficient estimators of population parameters under some realistic conditions. Out of many ratio, product and regression methods of estimation are good examples in this context.
Ratio Estimators in Simple Random Sampling Using Information on Auxiliary Attribute
Some ratio estimators for estimating the population mean of the variable under study, which make use of information regarding the population proportion possessing certain attribute, are proposed.
Improvement in Estimating Population Mean using Two Auxiliary Variables in Two-Phase Sampling
This study proposes improved chain-ratio type estimator for estimating population mean using some known values of population parameter(s) of the second auxiliary character. The proposed estimators have been compared with two-phase ratio estimator and some other chain ratio type estimators. The performances of the proposed estimators have been supported with a numerical illustration.
Auxiliary Information and a priori Values in Construction of Improved Estimators
This volume is a collection of six papers on the use of auxiliary information and a priori values in construction of improved estimators. The work included here will be of immense application for researchers and students who employ auxiliary information in any form.
Studies in Statistical Inference, Sample Techniques and Demography
This volume is a collection of five papers/chapters. Two chapters deal withproblems in statistical inference, two with inferences in finite population, and one deals with demographic problem. The ideas included here will be useful for researchers doing works in these fields.
Ratio-Product Type Exponential Estimator for Estimating Finite Population Mean Using Information on Auxiliary Attribute
In practice, the information regarding the population proportion possessing certain attribute is easily available, see Jhajj et.al. (2006). For estimating the population mean Y of the study variable y, following Bahl and Tuteja (1991), a ratio-product type exponential estimator has been proposed by using the known information of population proportion possessing an attribute (highly correlated with y) in simple random sampling.
Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables
In this paper exponential ratio and exponential product type estimators using two auxiliary variables are proposed for estimating unknown population variance 2 yS . Problem is extended to the case of two-phase sampling. Theoretical results are supported by an empirical study.
