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Statistics Seminar
Department of Mathematical Sciences

DATE:Thursday, August 29, 2019
TIME:1:15pm – 2:15pm
SPEAKER:Qiqing Yu, Binghamton University
TITLE: A Note On Application Of The Kullback-Leibler Information Inequality


One often makes use of Shannon-Kolmogorov inequality in proving the consistency of the maximum likelihood estimator (MLE). The approach does not work when E(\ln f(X)) does not exist, where f is the density function of the random variable X. We consider several parametric distribution families where E(\ln f(X)) does not exist. We make use of the Kullback-Leibler (K-L) Information inequality in proving that the MLE is consistent.

seminars/stat/190829.txt · Last modified: 2019/08/24 10:43 by qyu