TY  - GEN
AU  - Zenkova,Zhanna N.
AU  - Musoni,Wilson
AU  - Tarima,Sergey S.
TI  - Minimum variance and minimum Kulback-Leibler mean estimation with a known quantile
KW  - кумулятивная функция распределения
KW  - выборочное среднее
KW  - Кульбака-Лейблера расхождение
KW  - квантили
KW  - статьи в сборниках
N1  - Библиогр.: 14 назв
N2  - This work compares two mean estimators, MV and MKL, which incorporate information about a known quantile. MV minimizes variance and MKL minimizes Kulback-Leibler divergence. Both estimators are asymptotically equivalent and normally distributed but dier at nite sample sizes. Monte-Carlo simulation studies show that MV has higher mean squared error than MKL in the majority of simulated scenarios. Authors recommend using MKL when a quantile of an underlying distribution is known
UR  - http://vital.lib.tsu.ru/vital/access/manager/Repository/koha:000564534
ER  -