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Technical Program

Paper Detail

Paper IDD5-S3-T3.3
Paper Title A Generalized notion of Sufficiency for Power-law Distributions
Authors Atin Gayen, M. Ashok Kumar, Indian Institute of Technology Palakkad, India
Session D5-S3-T3: Statistics
Chaired Session: Friday, 16 July, 22:40 - 23:00
Engagement Session: Friday, 16 July, 23:00 - 23:20
Abstract We propose a generalized notion of principle of sufficiency when the underlying inference method is not necessarily maximum likelihood. This notion is based on certain generalized likelihood functions that arise in robust inference problems. Particularly, in this paper, we consider the Basu et al. estimation \cite{BasuHHJ98J}. We identify the specific form of the probability distributions that have a fixed number of sufficient statistics with respect to this estimation. These distributions are power-law in nature and Student distributions are a part of this family.