ALMOST UNBIASED JACK-KNIFED RATIO TYPE ESTIMATOR OF POPULATION VARIANCE

Frost and Tamura (1982) established through extensive Monte Carlo study that the jack-knifing improves the accuracy of the point estimate and the reliability of the interval estimate. This motivated to propose an unbiased jack-knifed ratio type estimator for the estimation of population variance corresponding to the estimator proposed by Gupta and Mishra (2006). It retains the same mean square error with an additional feature of unbiasedness to first order of approximation and is expected to dominate the ratio type estimators in the population with high error rates and both over and understatement errors.