In this paper, a class of log-type estimator using the auxiliary information in form of variable is proposed. Double sampling technique has been considered as it is assumed that the auxiliary information about the 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 literature.
Digital Object Identifier (DOI)
Kumari, Chandni and Kumar Thakur, Ratan
"An Efficient Log-Type Class Of Estimators Using Auxiliary Information Under Double Sampling,"
Journal of Statistics Applications & Probability: Vol. 10
, Article 18.
Available at: https://dc.naturalspublishing.com/jsap/vol10/iss1/18