INSTRUCTOR: MOULINATH BANERJEE
INSTRUCTOR OFFICE HOURS: Tue & Thurs, 5:30 to 7:00 p.m., 451, West Hall. Class meets Tue & Thurs from 4:00 to 5:30 pm, 130 Dennison.
GSI AND GRADER INFO: Toshiya Hoshikawa(firstname.lastname@example.org). Office hours: 443 West Hall. Weds 5:45 - 7:15 pm.
EXAM SCHEDULE: Exam 1: Thursday, Feb 24 in class. Exam 2: Wednesday, April 27, 8:00 - 10:00 am.
Weightage scheme: 5 homeworks carrying 6 points each + Exam 1 carrying 30 points + Exam 2 carrying 40 points.
TEXT: Keener's book (relevant chapters 8,9 and partly 16, 17) + Ferguson's "A Course in Large Sample Theory" + Notes posted below. Other sources to be used now and then are: some of Wellner's notes below + Lehmann and Cassella (Point Estimation) + Lehmann and Romano (Testing Statistical Hypothesis) + Lehmann's "A Course In Large Sample Theory".
CONTENT: Modes of convergence of random variables, convergence in law and CLTs, delta method, asymptotics of maximum likelihood estimation, likelihood ratio statistics, contiguity theory, EM algorithm + other topics.
Stat 612 Notes: 0
Stat 612 Notes: 1
Stat 612 Notes: 2
Stat 612 Notes: 3
Invariance of information bounds and influence functions under reparametrization
Examples -- 1SUPPLEMENTARY NOTES: (courtesy Jon A. Wellner; also available on last semester's 610 webpage)
The Probability Background
Important distributions in Statistics.
Basic Large Sample Theory.
Lower Bounds For Estimation.
Efficient Likelihood Estimation and Related Tests.
Bayes Methods and Decision Theory.
Statistical Functionals and the Delta Method.
The Bootstrap and the Jackknife.
Sufficiency and Unbiased estimation.