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Activity Number: 303 - Recent Developments on Order-Related Designs and Inferences
Type: Topic Contributed
Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM
Sponsor: Korean International Statistical Society
Abstract #309675
Title: An Objective General Index and Its Generalizations
Author(s): Tomonari Sei*
Companies: The University of Tokyo
Keywords: convex optimization; diagonal scaling; factor model; general index; ordered categorical data; ranking
Abstract:

We provide a weighting method of multivariate data for making a ranking. The weight is determined in such a way that the index has positive correlation with all variables, where each variable is assumed to have the meaning that a larger value indicates higher score. The weighted sum is called the objective general index. Mathematically, the problem of finding the weight is equivalent to a diagonal scaling problem. Numerical values of them are obtained via convex optimization. The method is also explained by a factor model with special loading structure. Generalizations of the index to ordered categorial data and a separation problem are discussed.


Authors who are presenting talks have a * after their name.

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