Stat 471 Computational Statistics

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Stat 471 Computational Statistics Instructor
Moo K. Chung E-mail mchung_at_stat.wisc.edu http//
www.stat.wisc.edu/mchung Office  4382 CSS 
Tel [phone] Probabilistic
white fiber tracking in the diffusion tensor
magnetic resonance image (DT-MRI) of the brain
showing the white fibers passing through the
splenium of corpus callosum (Chung et al., 2003).
The process requires implementing Cholesky
factorization, kernel smoothing, Markov chains,
spatially adaptive filter and statistical
simulation. Most of these topics will be covered
in the course. Requirements  Stat/Math 309-310
or Stat 311-312 and basic understanding of
computer programming. Assignment problems and
project will require computer programming in
MATLAB, S/R or any other programming language.
Most topics are self contained. Topics
covered Data structure, statistical graphics,
random number generators, matrix algebra,
optimization, simulations, Markov chains, random
walks, Monte Carlo integration, Markov chain
Monte Carlo (MCMC). Gibbs sampler. bootstrap,
kernel methods, spatial statistics, linear and
optimal filters and other computation intensive
statistical procedures. Textbook Computational
statistics handbook with MATLAB, W. L. Martinez,
A.R.  Martinez, Chapman Hall/CRC,
2002 Additional reading Advanced statistical
computing course notes, Robert Gray, 2001. Monte
Carlo statistical methods, C.P. Robert, G.
Casella. Springer, 1999. Course Evaluation
Assignment 70 Project 30 or Assignment 50
Project 50. Students are required to submit
minimum 10 page (30) or 15 page (50) double 
spaced and typed report excluding figures and
computer codes by the last class day on topics
discussed during the class (projects done in
other class will not be accepted). For graduate
students from other department, you can do a
project in your own research area after
consultation.