STAT 671: Statistical Computing

	Professor Richard Levine
Office	GMCS 565
Office Hours	M 3:30-4:30; W 12:00-1:00
Office Hours during final exam week	T 2:30-3:30 W 11:00-12:00; F 11:00-12:00
Email	ralevine@sciences.sdsu.edu

 

Assignments	Handouts
HW #1	Introduction to Matlab laboratory Normal pdf pic; Normal variates pic Infant mortalities data
HW #2	RANDU handout
Practice in-class midterm Practice exam solutions	Random variate generation Cheng-Feast algorithm
Take home portion of the midterm	Markov chains handout
In class exam Solutions for in class exam	Gibbs sampler article Metropolis-Hastings algorithm article
HW #3 autocorr.m	Hastings algorithm example
Final exam OK city temperature data	Gibbs: pump failure data Gibbs: trivariate normal
	ANOVA diagnostic for MCMC Rstat article
	Rao-Blackwellization and importance sampling Rao-Blackwellization article
	Newton Raphson and EM algorithms
	EM algorithm article

Bibliography for Handouts:

• Casella, G. and George, E. (1992). Explaining the Gibbs Sampler. The American Statistician 46, 167 - 174.
• Casella, G. and Robert, C. P. (1996). Rao-Blackwellization of Sampling Schemes. Biometrika 83, 81-94.
• Cheng, R. C. H. and Feast, G. M. (1979). Some Simple Gamma Variate Generators. Applied Statistics 28, 290-295.
• Chib, S. and Greenberg, E. (1995). Understanding the Metropolis-Hastings Algorithm. The American Statistician 49, 327 - 335.
• Gelman, A. and Rubin, D. B. (1992). Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7, 457-472.
• Navidi, W. (1997). A Graphical Illustration of the EM Algorithm. American Statistician 51, 29-31.