Generalized Class of Estimators for Population Variance Using Auxiliary Attribute

Abstract

Singh and Kumar (A family of estimators of population variance using information on auxiliary attribute. Studies in sampling techniques and time series analysis, 2011) and Singh and Malik (Appl Math Comput 235:43–49, 2014) suggested some estimators for estimating the population variance using an auxiliary attribute. This paper suggests a generalized class of estimators based on the adaption of the estimator presented by Koyuncu (Appl Math Comput 218:10900–10905, 2012) for population variance using information on an auxiliary attribute in simple random sampling. The properties of the suggested class of estimators are derived and asymptotic optimum estimator identified with its properties. The large numbers of known estimators are member of the suggested generalized class and it has been shown that proposed generalized class of estimators are more efficient than usual unbiased estimator, ratio, exponential ratio and regression estimator, estimators due to Singh and Malik (Appl Math Comput 235:43–49, 2014) and Singh and Kumar (A family of estimators of population variance using information on auxiliary attribute. Studies in sampling techniques and time series analysis, 2011) using information on auxiliary attribute. In addition, theoretical results are supported by an empirical study and findings are encouraging and support the soundness of present study.