@article{MAKHILLJMMS202014428217,
    title = {A Class of Modified Calibration Ratio Estimators of Population Mean with Known Coefficient
of Kurtosis in Stratified Double Sampling},
    journal = {Journal of Modern Mathematics and Statistics},
    volume = {14},
    number = {4},
    pages = {55-60},
    year = {2020},
    issn = {1994-5388},
    doi = {jmmstat.2020.55.60},
    url = {https://makhillpublications.co/view-article.php?issn=1994-5388&doi=jmmstat.2020.55.60},
    author = {Etebong and},
    keywords = {percentage relative efficiency,optimum conditions,large sample approximation,calibration constraint,Auxiliary information},
    abstract = {This study proposes a class of ratio estimators
of mean for calibration estimation that is more precise and
efficient than the linear regression estimator under the
stratified double sampling using coefficient of kurtosis of
auxiliary variable. Some well-known estimators are
obtained under certain prescribed conditions and shown
to be special members of this class of estimators.
Analytical and numerical results proved the efficacy of
the new class of estimators over all existing modified
estimators in stratified double sampling with appreciable
gains in efficiency at its optimum condition.}
    }