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The maximum "mean power" likelihood estimation procedure (proposed by [Basu et al., Biometrika, 1998]) is a robust variant of the maximum likelihood estimation procedure. Given iid samples coming from an unknown distribution, a member of a given parametric family of distributions, the mean power likelihood estimation procedure is to find the parameter of the distribution that is closest, in a particular sense, to the empirical distribution of the samples. One may view the resulting distribution as a "projection" of the empirical distribution on the parametric family. In this talk, I will highlight the geometry associated with this projection. I will also discuss a simplified computation procedure, one that is suggested by the geometric view point, when the estimation is of the parameter of a power-law family (this is joint work with M. Ashok Kumar). arXiv:1410.5550
Biography: Rajesh Sundaresan is an associate professor at the ECE department of IISc Bangalore.
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