期刊名称：Journal of Statistical Theory and Applications (JSTA)
电子版ISSN：1538-7887
出版年度：2018
卷号：17
期号：2
页码：263-272
DOI：10.2991/jsta.2018.17.2.6
语种：English
出版社：Atlantis Press
摘要：Marshall and Olkin [Biometrika199784641652] introduced a method for constructing a new distribution by adding a new parameter, called tilt parameter, to a parent distribution. It is observed that adding this parameter leads to a more flexible model than the parent model. In this paper, different estimators for tilt parameter as a major parameter are presented. Their performances are compared using Monte Carlo simulations. Hypothesis testing and interval estimation of tilt parameter using Rao score test is discussed.
关键词：Tilt parameter;Marshall-Olkin distribution;Maximum likelihood estimation;Maximum spacing estimation;Least-squares estimation;coverage probability
