This course is the third semester of the required four semester applied statistics sequence in the School of Statistics Ph.D. program. To enroll in this course you must be a second-year Ph.D. student in statistics or have permission of the instructor.

The course meets 2:30-3:20 MWF (09/08/2009 - 12/16/2009) VinH 20.

Handouts

• Sept. 9, 2009 Course syllabus.
• Sept. 9 linear mixed model. R commands: fishgrowth.R.
• Sept. 11 generalized linear mixed model. R commands: glmm1.R.
• Sept. 14 smoothing with one predictor. R commands: smoothing.R.
• Sept. 23 additive models. R commands: gam.R.
• Sept. 30 generalized additive models. R commands: gam2.R.
• Oct. 2 L1 models. R commands: L1.R. quantreg vignette: rq.pdf, quantreg manual quantreg.pdf.
• Oct. 5 Recursive partitioning: lpart.R Here is a link (U of M only) to a book by R. Berk that has extended presentations of these topics: Statistical Learning from a Regression Perspective.
• Oct. 16 Variable Selection and Regularization. R commands: lasso.R.
• Nov. 6 Manova. R commands: manova.R.
• Nov. 9 Chapter 8, low-dimensional approximations. R commands: chap8.R.
• Nov. 11 Chapter 9, PCA. R commands: chap9.R.
• Nov. 13 Chapter 10, Factor analysis. R commands: chap10.R.
• Nov. 18 Chapter 11, Clustering. R commands: chap11-clustering.R
• Nov. 23 Chapter 12, LDA. R commands: chap12-lda.R.

Assignments

• Due Sept. 18 Assignment 1.
• Due Sept. 25 Assignment 2.
• Due Oct. 7 Assignment 3.
• Due Oct. 14 Assignment 4.
• Due Oct. 21 Assignment 5.
• Due Nov. 6 Assignment 6.
• Due Nov. 16 Assignment 7.
• Due Nov. 30 Assignment 8.

Data

• wolf data.
• roads data.
• NDCS data.