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This paper addresses the problem of estimating the population mean Y... of the study variable Y using information on population parameters associated with the auxiliary attribute Φ. We have suggested a class of estimators of population Y... mean using auxiliary attribute. Expressions of bias and mean squared error of the suggested class of estimators have been derived up to first order of approximation. Optimum condition is obtained at which the proposed class of estimators has minimum mean squared error. Theoretical findings are also supported through the aid of a numerical illustration. [ABSTRACT FROM AUTHOR]

In this paper we have considered the problem of estimating the population mean Y of the study variable y using information on auxiliary variable x in stratified random sampling. A class of estimators has been proposed. The bias and mean squared error have been obtained up to first degree of approximation. Optimum condition is obtained in which the proposed class of estimators has least mean squared error. We have also compared the proposed class of estimators with some existing estimators. An empirical study is carried out in support of the present study. [ABSTRACT FROM AUTHOR]

This article introduces an upgraded family of dual estimators for the population mean of main variable using some known supplementary information. To construct the family of estimators, a suitable transformation on the study variable as well as auxiliary variable has been used. The sampling features of the proposed class of estimators have been studied up to first order under large sample approximation. Several existing estimators have been observed and found as particular members of the proposed family of estimators. The optimum values of the characterizing scalars of the suggested family of estimators are obtained through the method of maxima–minima. The least value of the Mean Squared Error (MSE) of the proposed class of estimators is also obtained for these optimal values of the characterizing constants. The proposed family of estimators is compared theoretically with the other competing estimators of population mean. To judge the performance of the suggested family of estimators over others, numerical illustration has also been given. The estimator with minimum MSE is recommended for practical utility in different areas of applications. The results show the suggested estimator performs better than the competing estimators, therefore it may be used in different applications. [ABSTRACT FROM AUTHOR]

This paper aims to discuss the problem of estimating the population mean Y ¯ of the study variable y using information on an auxiliary variable x in circular systematic sampling (CSS) scheme along with the non-response problem. We have suggested a generalized family of estimators for population mean Y ¯ of y based on auxiliary variable x. We have derived the expressions for bias and mean squared error of the proposed family of estimators upto first order of approximation. Optimum conditions are obtained in which the suggested family of estimators has the least mean squared error. It has been shown that the proposed family of estimators is better than usual unbiased estimator, ratio estimator and the regression estimator. An empirical study is provided to show that the suggested family of estimators is better than the ratio and regression estimators. [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]

The paper advocates the problem of estimating population mean on the current (second) occasion using auxiliary information in successive sampling over two-occasions. A class of estimators based on transformed auxiliary variable is derived. The bias and mean square error of the proposed estimator have been obtained. The suggested estimator has been compared with simple mean estimator when there is no matching and the optimum estimator, which is a combination of the means of the matched and unmatched portion of the sample at the second occasion. Optimum replacement policy and the efficiency of the suggested estimator have been discussed. Numerical Illustration is given in support of the present study. [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]

This paper considers the problem of estimating the population varianceS2yof the study variableyusing the auxiliary information in sample surveys. We have suggested the (i) chain ratio-type estimator (on the lines of Kadilar and Cingi (2003)), (ii) chain ratio-ratio-type exponential estimator and their generalized version [on the lines of Singh and Pal (2015)] and studied their properties under large sample approximation. Conditions are obtained under which the proposed estimators are more efficient than usual unbiased estimators2yand Isaki (1893) ratio estimator. Improved version of the suggested class of estimators is also given along with its properties. An empirical study is carried out in support of the present study. [ABSTRACT FROM PUBLISHER]

This article considers the problem of estimating the finite population meanof the study variableyusing information on an auxiliary variablexin presence of non-response. We have suggested two-parameter ratio-product-ratio estimator in two different situations and their properties are studied under large sample approximation. We have presented comparisons of the proposed two-parameter ratio-product-ratio estimator with usual unbiased estimatorand ratio estimators (tR1,tR2). An empirical study is carried out in support of the present study. [ABSTRACT FROM AUTHOR]

This paper considers the problem of estimating the finite population mean Y of the study variable using information on two auxiliary variables (x, z) . A family of ratio-cum-product estimators for population mean Y has been suggested. It has been shown that the usual unbiased estimator y , ratio estimator, product estimator, dual to ratio estimator and dual to product estimator due to Srivenkatramana (1980) and Bandyopadhyaya (1980), Singh et al's (2005, 2011) estimator, Tailor et aTs (2012) estimator, Vishwakarma et al's (2014) estimator and Vishwakarma and Kumar (2015) estimator are members of the suggested family of estimators. In addition to these estimators, various unknown estimators are shown to be the member of the suggested family of estimators. The bias and mean squared error of the proposed family are obtained under large sample approximation. Efficiency comparisons are made to demonstrate the performance of the suggested family over other existing estimators. An empirical study is carried out in support of the present study. [ABSTRACT FROM AUTHOR]

This paper considers a generalized ratio-cum-product estimator of population mean in systematic sampling using auxiliary information in sample surveys. A large number of estimators of different parameters of the study variables based on auxiliary information can be viewed as a member of suggested class of estimators. The bias and mean squared error of the proposed class of estimator have been obtained under large sample Approximation. Optimum conditions are obtained for which the proposed class of estimators has minimum mean squared error. It has been proved theoretically that the suggested class of estimators at its optimum condition is more different than the regression estimator in systematic sampling. An empirical study is carried out in support of the present study. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of estimating the population varianceS2yof the study variableyusing auxiliary information in sample surveys. We have suggested a class of estimators of the population varianceS2yof the study variableywhen the population varianceS2xof the auxiliary variablexis known. Asymptotic expressions of bias and mean squared error (MSE) of the proposed class of estimators have been obtained. Asymptotic optimum estimators in the proposed class of estimators have also been identified along with its MSE formula. A comparison has been provided. We have further provided the double sampling version of the proposed class of estimators. The properties of the double sampling version have been provided under large sample approximation. In addition, we support the present study with aid of a numerical illustration. [ABSTRACT FROM AUTHOR]

In the present article, we have proposed some classes of estimators based on transformed auxiliary variable. The biases and mean squared errors (MSEs) of the proposed estimators have been obtained. The proposed estimators have been compared with simple mean estimator when there is no matching and the optimum estimator, which is a combination of the means of the matched and unmatched portion of the sample at the second occasion. Optimum replacement policy and the efficiency of the proposed estimators have been discussed. Theoretical results are well supported with an empirical study. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of estimating a general parameter using information on an auxiliary variableX. We have suggested a class of exponential-type ratio estimators for the parameter and its properties are studied. It is identified that the estimators due to Upadhyaya et al. [Journal of Statistical Theory and Practice (2011), 5(2), 285–302] and Yadav and Kadilar [Revista Columbiana de Estadistica, (2013), 36(1), 145–152] are members of the proposed estimator. We have also shown that the suggested estimator is more efficient than the estimators of Upadhyaya et al. (2011) and Yadav and Kadilar (2013). Numerical illustration is provided in support of the present study. [ABSTRACT FROM AUTHOR]

This article suggests the class of estimators of population mean of study variable using various parameters related to an auxiliary variable with its properties in simple random sampling. It has been identified that the some existing estimator/classes of estimators are members of suggested class. It has been found theoretically as well as empirically that the suggested class is better than the existing methods. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a class of estimators of finite population variance using known values of parameters related to an auxiliary variable such as quartiles and its properties are studied in simple random sampling. The suggested class of ratio-type estimators has been compared with the usual unbiased, ratio estimators and the class of ratio-type estimators due to Singhet al.[Improved estimation of finite population variance using quartiles, Istatistik – J. Turkish Stat. Assoc. 6(3) (2013), pp. 166–121] and Solankiet al.[Improved ratio-type estimators of finite population variance using quartiles, Hacettepe J. Math. Stat. 44(3) (2015), pp. 747–754]. An empirical study is also carried out to judge the merits of the proposed estimator over other existing estimators of population variance using natural data set. It is found that the proposed class of ratio-type estimators ‘’ is superior to the usual unbiased estimatorand the estimators recently proposed by Singhet al.[Improved estimation of finite population variance using quartiles, Istatistik – J. Turkish Stat. Assoc. 6(3) (2013), pp. 166–121] and Solankiet al.[Improved ratio-type estimators of finite population variance using quartiles, Hacettepe J. Math. Stat. 44(3) (2015), pp. 747–754]. [ABSTRACT FROM AUTHOR]

We suggested the class of estimators of the population mean with its bias and mean square error. It has been shown that the suggested class is more efficient than the usual unbiased, ratio, product and regression estimators and estimators due to Bahl and Tuteja (1991), Singh et al. (2009), and Upadhyaya et al. (2011). In addition an empirical study also carried out to and founded that the members of suggested family also have improvement over Grover and Kaur (2011) and Shabbir and Gupta (2011) classes. Two-phase (double) sampling version of the proposed class was also given. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of estimating the population mean of the study variable y using information on an auxiliary variable x. A class of Exponential-Type Estimators has been suggested along with its properties under large sample approximation. It is identified that the usual Unbiased Estimator, Product-Type and Ratio-Type Exponential Estimators are members of the proposed class of Exponential-Type Estimators. It has been shown that the proposed class of Exponential-Type Estimators is more efficient than the usual Unbiased Estimator and some existing Estimators. An empirical study is carried out in support of the present study. [ABSTRACT FROM AUTHOR]

This article suggests an improved class of estimators for estimating the general population parameter using information on an auxiliary variable. The properties of the suggested class of estimators have been studied under large sample approximation. The general results are then applied to estimate the population coefficient of variation of study variable using auxiliary information. An empirical study is given in support of the theoretical results. [ABSTRACT FROM PUBLISHER]

In this article, we have suggested some classes of estimators for estimating finite population median using information on an auxiliary variable. To study the properties of suggested classes of estimators under large sample approximation, a generalized class of estimators has been suggested with its properties. It has been shown that the suggested classes of estimators are more efficient than other existing estimators. The results have been illustrated through an empirical study. [ABSTRACT FROM PUBLISHER]

This article addresses the problem of estimating the population mean in stratified random sampling using the information of an auxiliary variable. A class of estimators for population mean is defined with its properties under large sample approximation. In particular, various classes of estimators are identified as particular member of the suggested class. It has been shown that the proposed class of estimators is better than usual unbiased estimator, usual combined ratio estimator, usual product estimator, usual regression estimator and Koyuncu and Kadilar (2009) class of estimators. The results have been illustrated through an empirical study. [ABSTRACT FROM PUBLISHER]

This article addresses the problem of the estimation of the population meanof the study variable y using auxiliary variable x in stratified random sampling. Classes of ratio and product exponential type estimators are proposed. The biases and mean squared errors of the suggested estimators are obtained upto the first order of approximation. Conditions are obtained under which the proposed estimators are better than usual unbiased estimator, conventional combined ratio and product estimators and Singh et al. (2008) estimators. Asymptotic optimum estimators (AOEs) in the proposed classes of estimators are identified alongwith their mean squared errors formulae. Estimators based on estimated optimum values are obtained with their mean squared errors expressions. An empirical study has been carried out to examine the merits of the suggested estimators over others. [ABSTRACT FROM AUTHOR]

Starting from the Singh et al. [28] [Current Science 57: 1331-1334] difference estimator, we define a class of estimators for the unknown variance of a survey variable on the line of Diana et al. [7] [Stat Methods Appl DOI 10.1007/s10260-010-0156-6] when auxiliary variable is available. The bias and mean square error of the estimators belonging to the class of estimators are derived and the expressions for the optimum parameters minimizing the asymptotic mean square error are given in closed form. A simple condition allowing us to improve the usual difference estimator due to Das and Tripathi [6] [Sankhya C 40: 139-148] is derived. Finally, in order to judge the merits of some estimators with the usual difference one, an empirical study is carried out. [ABSTRACT FROM AUTHOR]

Abstract: This paper addresses the problem of estimating the population mean with known population proportion of an auxiliary variable. A class of estimators is defined which includes the estimators recently proposed by Shabbir and Gupta (2007) and Abd-Elfattah et al. (2010) . The usual unbiased estimator and Naik and Gupta (1996) estimator are also the member of the proposed class of the estimators. The bias and mean square error (MSE) expressions of the proposed class are obtained up to first order of approximation. Asymptotically optimum estimator (AOE) in the class of estimators is identified alongwith its mean square error formula. The correct MSE and minimum MSE expressions of Shabbir and Gupta (2007) estimator are also given. It has been shown that the proposed class of estimators is more efficient than the usual unbiased estimator, usual linear regression estimator and estimators/classes of estimators due to Naik and Gupta (1996) , Jhajj et al. (2008) , Shabbir and Gupta (2007) estimator, Singh et al. (2008) and Abd-Elfattah et al. (2010) . The double sampling version of the proposed class of estimators is proposed alongwith its properties. Numerical illustrations are given in support of the present study. [Copyright &y& Elsevier]

In this paper we have considered the problem of estimating the general population parameter in the presence of random non-response using an auxiliary variable in three different situations. A general family of estimators of the parameter has been suggested and its properties are studied. In particular, the problem of estimating the population coefficient of variation has been considered. [ABSTRACT FROM AUTHOR]

In this paper we have suggested a double sampling version of Sahai [10] estimator using simple random sampling without replacement (SRSWOR) at both phases and its properties are studied. The estimator is also compared with simple mean per unit for a given cost of the survey. An empirical study is carried out to demonstrate the performance of suggested estimator over usual estimators. [ABSTRACT FROM AUTHOR]