**Problem of the Week**

**Math Club**

**BUGCAT 2020**

**Zassenhaus Conference**

**Hilton Memorial Lecture**

**BingAWM**

seminars:stat:190829

Statistics Seminar

Department of Mathematical Sciences

DATE: | Thursday, August 29, 2019 |
---|---|

TIME: | 1:15pm – 2:15pm |

LOCATION: | WH 100E |

SPEAKER: | Qiqing Yu, Binghamton University |

TITLE: | A Note On Application Of The Kullback-Leibler Information Inequality |

**Abstract**

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

Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Noncommercial-Share Alike 3.0 Unported