Bridging the gap: a parametric approach to a non parametric problem

• Activity Number: 262
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Section on Nonparametric Statistics
• Author(s): Mayer Alvo*
• Companies: University of Ottawa
• Keywords: Rao score test ; ranking data ; Penalized likelihood ; Spearman ; Kendall ; von Mises distribution

Abstract

In the parametric setting, the notion of a likelihood function forms the basis for the development of tests of hypotheses and estimation of parameters. Tests in connection with the analysis of variance stem entirely from considerations of the likelihood function. On the other hand, the empirical likelihood method which is entirely data driven, presents an alternative to the parametric notion. In the present article, we define a likelihood function motivated by characteristics of the ranks of the data. Such a likelihood function can be fruitfully used in several problems in non parametric statistics involving the use of ranks.