A New Exponential Ratio-Type Estimator for Population Variance with Linear Combination of Two Auxiliary Attributes (original) (raw)

A new improved class of ratio-product type exponential estimators of the population variance

Scientia Iranica

Several auxiliary information-based estimators of the population variance are available in the existing literature of survey sampling. Mostly, these estimators are based on conventional dispersion measures of the auxiliary variable. In this study, a generalized class of ratio-product type exponential estimators of the population variance is proposed which integrates the auxiliary information on non-conventional dispersion measures under simple random sampling in the ratio-type exponential class of estimators. The performance of the proposed estimators is compared, theoretically and numerically, with the several existing estimators of the population variance. It is established that the proposed class of estimators outperforms the existing estimators in terms of the lower mean square and relative root mean square errors. Moreover, the percentage relative efficiency of the proposed estimators is much higher as compared to their counterparts.

Improved Ratio Type Estimators Using Auxiliary Attribute for Population Variance

International Journal of Science and Research (IJSR), 2020

This paper proposes a family of estimators based on the auxiliary information on a attribute. The bias and mean squared error are obtained up to the first order of approximation. The theoretical comparison are also supported by numerical examples based on the two natural populations, showing the superiority of the suggested family of estimators, both theoretically as well as empirically over estimators available in literature.

Estimation of Finite Population Variances using Auxiliary Attribute in Sample Surveys

Journal of Advanced Computing, 2015

Singh and Kumar (2011) suggested some estimators for estimating the population variances using an auxiliary attribute. This paper suggest some improved class of estimators of population variance using auxiliary information in form of attribute of the study variable Y based on arithmetic mean, geometric mean and harmonic mean of the usual unbiased estimator, usual ratio estimators and estimators due to Singh and Kumar (2011) in case of simple random sampling. The expressions of bias and MSEs have been derived up to the first order of approximation. It has been shown that the performance of the proposed estimators is better than the usual unbiased estimator, usual ratio estimators and estimators due to Singh and Kumar (2011). In addition, an empirical study is carried out in the support of theoretical results.

A Family of Estimators of Population Variance Using Information on Auxiliary Attribute

This paper proposes some estimators for the population variance of the variable under study, which make use of information regarding the population proportion possessing certain attribute. Under simple random sampling without replacement (SRSWOR) scheme, the mean squared error (MSE) up to the first order of approximation is derived. The results have been illustrated numerically by taking some empirical population considered in the literature.

A Ratio-cum-Dual to Ratio Estimator of Population Variance Using Qualitative Auxiliary Information Under Simple Random Sampling

Mathematical Journal of Interdisciplinary Sciences, 2013

In this paper we have proposed a class of ratio-cum-dual to ratio estimators for estimating population variance of the variable under study, using known values of some population parameters of auxiliary variable, which is available in the form of an attribute. The expressions for the bias and mean squared error of the proposed estimators have been derived upto the first order of approximation. A comparison has been made with some well known estimators of population variance available in the literature when auxiliary information is in qualitative form. It has been shown that the proposed estimator is better than the existing estimators under the optimum condition. For illustration an empirical study has been carried out.

On Modification of Some Ratio Estimators using Parameters of Auxiliary Variable for the Estimation of the Population Mean

Oriental Journal of Physical Sciences, 2023

Some existing estimators based on auxiliary attribute have been proposed by many authors. In this paper, we use the concept of power transformation to modify some existing estimators in order to obtain estimators that are applicable when there is positive or negative correlation between the study and auxiliary variable. The properties (Biases and MSEs) of the proposed estimators were derived up to the first order of approximation using Taylor series approach. The efficiency comparison of the proposed estimators over some existing estimators considered in the study were established. The empirical studies were conducted using existing population parameters to investigate the proficiency of the proposed estimators over some existing estimators. The results revealed that the proposed estimators have minimum Mean Square Errors and higher Percentage Relative Efficiencies than the conventional and other competing estimators in the study. These implies that the proposed estimators are more efficient and can produce better estimates of the population mean compared to the existing estimators considered in the study.

EFFICIENT CLASS OF ESTIMATORS FOR ESTIMATING THE POPULATION VARIANCE USING AUXILIARY VARIABLE AND ATTRIBUTE

A family of log-type estimators using information on auxiliary information has been proposed for estimating the population variance of the study variable. It has been shown that these families of log-type estimators have lesser mean square error under the optimum values of the characterizing scalars as compared to some of the commonly used estimators available in the literature. Further, a comparative study is performed to judge the efficiency of proposed estimator. A numerical study is included as an illustration for the proposed work.

A New Chain Ratio-Ratio-Type Exponential Estimator Using Auxiliary Information In Sample Surveys

This paper advocates the problem of estimating the finite population mean using auxiliary information in sample surveys. We have suggested a new chain ratio-ratio-type exponential estimator and its properties are studied up to first degree of approximation. It has been shown that the proposed estimator is more efficient than the usual unbiased estimator, classical ratio estimator, Bahl and Tuteja [1] ratio-type exponential estimator and Kadilar and Cingi [3] chain ratio-type estimator under very realistic condition. Generalized version of the suggested chain ratio-ratio-type estimator is also given along with its properties. An empirical study is given in support of the present study.

An Advanced Class of Log-Type Estimators for Population Variance Using an Attribute and a Variable

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING RESEARCH AND DEVELOPMENT, 2020

In this paper, a class of log-type estimator using the auxiliary information in form of attribute as well as variable is proposed. Double sampling technique has been considered as it is assumed that the auxiliary information about the auxiliary attribute as well as auxiliary variable is unknown. Bias and mean squared error has been found up to the first order of approximation. The proposed classes are compared to some commonly used estimators both theoretically as well as empirically and they perform better than commonly used estimators available in the literature.