Stat 562, Spring 2011
Instructor : Bing Li; Telephone: 865 1952; Office: 410 Thomas Building.
Time & Place : MWF 1:25 pm – 2:15 pm at 201 Wagner.
Office hours : MWF 2:30 pm – 3:30 pm.
References :
1.
Theory of Point Estimation
, Erich Lehmann, Springer, 1997.
2.
Approximation Theorems of Mathematical Statistics , Robert Serfling, John Wiley
& Sons, 1980.
3.
A Course in Large Sample Theory
, Thomas S. Ferguson, Chapman and Hall,
1996.
4.
Quasi-likelihood and its application
, Christopher Heyde.
5.
Asymptotic Statistics
, van der Vaart, Cambridge University Press, 1998.
6.
Efficient and Adaptive Estimation for Semiparametric Models
, Peter J. Bickel,
Chris A. J. Klaassen, Ya’acov Ritov, Jon A. Wellner. The Johns Hopkins Univer- sity Press. 1993.
7.
Tensor Methods in Statistics
, Peter McCullagh. Chapman and Hall, 1987.
Examinations : There will be a midterm and a final exam. They will be closed book and in class. You may bring a page of prepared notes for each exam.
Assignments : Homework will be assigned and graded every two weeks.
Evaluation : Midterm 30 %. Final 45%. Homework 25%.
Course coverage :
Preliminaries. Asymptotic Theory for Maximum Likelihood Estimation. Asymptotic
Theory for Estimating Equations. Asymptotic chi-square tests. Quasilikelihood, GLM, GEE.
Local Asymptotic Analysis of regular estimators. Local Asymptotic Analysis of regular tests. von-Mises expansion of statistical functionals.
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All Penn State and Eberly College of Science policies regarding academic integrity apply to this course. See http://www.science.psu.edu/academic/Integrity concerning academic in- tegrity for details.