Search

In this paper we have suggested a class of estimators of population mean of sensitive variable under optional randomized response technique as reported in Gupta et al (2014). We have obtained the mean squared error (MSE) of the suggested class of estimators up to the first order of approximation. The optimum conditions are obtained at which the (MSE) of the proposed class of estimators is minimum. An empirical study is carried out to show the performance of the suggested class of estimators over existing estimators .It is found that the performance of proposed class of estimators is better than the existing estimators including Grover and Kaur (2019) [ABSTRACT FROM AUTHOR]

In this paper we consider a two parameter ratio-product-ratio estimator for estimating population mean in case of post stratification following the estimator due to Chami et al (2012). The bias and mean squared error of proposed estimator are obtained to the first degree of approximation. We derive conditions under which the proposed estimator has smaller mean squared error than the sample mean psy, ratio estimator) (ps R y and product estimators P(ps) y. Empirical studies gives insight on the magnitude of the efficiency of the estimator developed. [ABSTRACT FROM AUTHOR]

In this paper we have considered the problem of estimating the population mean using auxiliary information in sample surveys. A class of dual to ratio estimators has been defined. Exact expressions for bias and mean squared error of the suggested class of dual to ratio estimators have been obtained. In particular, properties of some members of the proposed class of dual to ratio estimators have been discussed. It has been shown that the proposed class of estimators is more efficient than the sample mean, ratio estimator, dual to ratio estimator and some members of the suggested class of estimators in some realistic conditions. Some numerical illustrations are given in support of the present study. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of estimating the population mean Y¯ of the study variable y using information on transformed auxiliary variables. In addition to many, Yasmeen et al(2015) estimator shown to be the members of the suggested classes of estimators. We have derived the bias and mean squared error (MSE) of the suggested classes of estimators to the first degree of approximation. We have obtained the optimum conditions for which the suggested classes of estimators have minimum mean squared errors. It has been shown that the proposed classes of estimators are more efficient than the estimators recently envisaged by Yasmeen et al (2015)and other existing estimators. [ABSTRACT FROM AUTHOR]

This paper suggests a two-parameter ratio-product-ratio type exponential estimator for a finite population mean in simple random sampling without replacement (SRSWOR) following the methodology in the studies of Singh and Espejo (2003) and Chami et al (2012). The bias and mean squared error of the suggested estimator are obtained to the first degree of approximation. The conditions are obtained in which suggested estimator is more efficient than the sample mean, classical ratio and product estimators, ratio-type and product type exponential estimators. An empirical study is given in support of the present study. [ABSTRACT FROM AUTHOR]

In this paper, a simple and obvious procedure is presented that allows to estimate the population proportion π possessing sensitive attribute using simple random sampling with replacement (SRSWR). In addition to T, the probability that a respondent truthfully states that he or she bears a sensitive character when experienced in a direct response survey. An efficiency comparison is carried out to investigate in the performance of the proposed method. It is found that the proposed strategy is more efficient than Warner's (1965) as well as Huang's (2004) randomized response techniques under some realistic conditions. Numerical illustrations and graphical representations are also given in support of the present study. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of estimating the finite population mean using auxiliary information in simple random sampling. Firstly we have suggested a correction to the mean squared error of the estimator proposed by Gupta and Shabbir (2008). Later we have proposed a ratio type estimator and its properties are studied in simple random sampling. Numerically we have shown that the proposed class of estimators is more efficient than different known estimators including Gupta and Shabbir (2008) estimator. [ABSTRACT FROM AUTHOR]