In-type estimators for the population variance in stratified random sampling

In the stratified random sampling, the variance estimators are popularly proposed by using the ratio, product, regression, and exponential type estimators. Up to now, an alternative to these estimator types has not been considered. In this article, we consider -function while estimating the population variance for the first time in literature. We propose the variance estimators using the separate method in the stratified random sampling. We derive the mean squared error (MSE) for the proposed estimators and find that the proposed estimators are more efficient than the estimators in literature. Besides, numerical illustrations and a simulation study support our findings in theory.