Lecture I (February 15)
Lecture II (February 22)
Please note that density function for the Weibull and Frechet family of distributions are wrong in the video lecture and class notes. I will correct it in the handwritten notes (to be uploaded soon).
Video lecture Part I Video Lecture Part II
Class notes Handwritten notes (To be updated)
Lecture III (March 01)
Lecture IV (March 08) simulation study
Simulation and codes Video lecture
Lecture V (March 22) Khintchine's theorem and max-domain of attraction for the Gumbel distribution
Lecture VI (Max-domain of attraction for Frechet and Weibull distribution)
Lecture VII (Exceedences and Extremes)
Lecture VIII
Lecture IX
Lecture X
Lecture XI (Statistical rationale for Maximum Likelihood Estimation)
Lecture XII (Estimators with good large-sample performance)
Lecture XIII (Information inequality and efficiency of MLE: Part I)
Lecture XIV (Cam\'{e}r's weak consistency of MLE)
Some interesting articles and presentations on the likelihood-based inference:
The Epic Story of Likelihood - Stephen Stigler
IMS Le Cam Lecture Maximum Likelihood in modern times: the ugly, the bad, and the good - Jon Wellner
A survey of Maximum Likelihood Estimation - Nordman
Apparent Anomalies and Irregularities in Maximum Likelihood Estimation - C. R. Rao (Criticism of MLE)
Lecture XV (Wald's strong consistency and asymptotic normality of MLE)
Lecture XVI (Consisent estimation: going beyond the parametric families)