LECTURE NOTES AND COURSE HANDOUTS (2006):  

Syllabus

Chapter 1: The Canonical Normal Means Estimation Problem [last rev. 9/28/06 + minor rev. to 10/10/06]

Chapter 2: Bayes Estimators, Minimaxity and Admissibility [last rev. 9/28/06]

Chapter 3: The Three Siblings [version of 10/16/06 - needs further Exercises and minor revisions]

Chapter 4: Shrinkage in the Absence of Spherical Symmetry [version of 11/2; needs some corrections and additions]

References (through Chap 1) [last rev. 10/16/06]

Topics for Projects.pdf [last rev 9/18/06]

Baseball Data (K. Shirley)

Call Center service-times data

References:

        (I will include here a selection of harder to obtain references. Many of the other references in the lecture notes are available online through the Penn library via JSTOR, etc.)

    Stein, C. (1956). Inadmissibility of the usual estimator for the mean of a multivariate normal distribution. Proc. 3^rd Berk Symp Math. Statist. Prob. 1, Univ of Calif. Press, Berkeley, CA., 197-206.

    James, W. and Stein, C. (1961). Estimation with quadratic loss. Proc. 4^th Berk Symp Math. Statist. Prob. 1, Univ of Calif. Press, Berkeley, CA., 311-319.

    Brown, L. D. and Zhao, L. H. (2006). Estimators for Gaussian models having a block-wise structure. Preprint, available at www-stat.wharton.upenn.edu/~lbrown.

    Maruyama, Y. (1999). Improving on the James-Stein estimator. Statistics and Decisions, 14, 137-140.

    Maruyama, Y. (2004). Stein’s idea and minimax admissible estimation of a multivariate normal mean. Jour of Multiv. Anal., 88, 320-334.

    Maruyama, Y. (2006). An admissibility proof using an adaptive sequence of smoother improper priors approaching the target improper prior. manuscript.

    Brown, L. D. and Hwang, J. T. G. (1982). A unified admissibility proof. Statistical Decision Theory and Related Topics III, (S. Gupta and J. Berger, eds.), Vol 1, 205-230.

Handouts from previous year (2005):

    (These will be replaced by newly revised and re-edited files during the course of the semester.)

Chapter4: Multiple Regression Part I

Chapter4: Multiple Regression Part II

Chapter5: Random effects models Part I

Chapter5: Random effects models Part II

Last Updated: Nov 2, 2006