A non-iterative procedure for maximum likelihood estimation of the parameters of Mallows' model based on partial rankings

被引：2
|
作者：
Adkins, L [1 ]
Fligner, M [1 ]
机构：
[1] Marshall Univ, Dept Math, Huntington, WV 25755 USA
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1998年 / 27卷 / 09期
关键词：
ranking models; permutation data;
D O I：
10.1080/03610929808832223
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
The problem of maximum likelihood estimation of the parameters of Mallows' ranking model based on partial rankings (with a fixed number of tie groups) has been approached by Beckett (1992), applying the EM algorithm to estimate both the center and the scale parameter. This paper offers an alternative procedure for maximum likelihood estimation without relying an the EM algorithm: the center is estimated by minimizing the sum of the distances between the center and the observed partial rankings, and the scale parameter is estimated by solving a relatively simple equation.
引用
收藏
页码：2199 / 2220
页数：22
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