STAT 6304: Computational Heroy Science Hall, Room 127, Tue, Thur 9:30am - 10:50am Fall 2004 Instructor: Dr. H. K. Tony Ng Office: Heroy Science Hall, Room 106 Phone: (214) 768-2465 E-mail: [email protected] Url: http://faculty.smu.edu/ngh

Course Objectives:

The aim of this course is to give graduate students a solid foundation of computational statis- tics, which they will use in other courses and their research at SMU. This course introduces some computational methods in statistics with emphasis on the usage of statistical software packages, statistical simulation, numerical methods, and related topics. It is assumed that each student has a working knowledge of either Fortran or C programming languages.

After this course, the student should be able to...

• use S-plus to preform statistical analysis;

A • use LTEX to type technical reports and papers; • find appropriate information from the library, internet, or other sources when using com- puter software;

• use different methods to solve an optimization problem;

• apply some efficient computer algorithms in linear models;

• use Monte Carlo methods to solve statistical problems;

• plan and implement a statistical simulation study in an efficient way;

• interpret the results from a simulation study. Method of evaluation:

Assignments 25% Test 1 20% Test 2 20% TermProject(Report) 20% Term Project (Presentation) 15%

1 Office hours:

Tue 2:00pm - 3:00pm; Wed 11:00am - 12:00nn

You are also welcome to drop in my office anytime. You may also set up an appointment by e-mail. Computer Usage Policy:

Attention is drawn to the SMU computer usage policy. Please read the policy carefully and keep that in mind whenever you are using your computer account. http://www.smu.edu/policy/S12/computer.html

Late Work Policy:

Late work will not be accepted without prior authorization. If you have a conflict or difficulties, please feel free to come and talk to me and we can try to postpone the due date.

Academic Ethics and Dishonesty:

Discussion of assignment questions are strongly encouraged, however, students are expected to create, edit and print out their own assignments and take tests without outside assistance. All work is expected to be your own. Exchanging code or work whether it is electronically or by exchanging printouts is considered as scholastic dishonesty in this class.

Religious Observance:

Religiously observant students wishing to be absent on holidays that require missing class should notify their professors in writing at the beginning of the semester, and should discuss with them, in advance, acceptable ways of making up any work missed because of the absence. (See University Policy No. 1.9.)

Disability Accommodations:

Students needing academic accommodations for a disability must first contact Ms. Rebecca Marin, Coordinator, Services for Students with Disabilities (214-768-4557) to verify the disabil- ity and establish eligibility for accommodations. They should then schedule an appointment with the professor to make appropriate arrangements. (See University Policy No. 2.4.)

2 Course Content:

Week Date Topics Remarks 1 19 Aug. Course Introduction 2 24 Aug. Introduction to UNIX 26 Aug. Introduction to S and S-PLUS 3 31 Aug. Introduction to MS Excel 2 Sept. Graphics in S 4 7 Sept. More on graphics in S Assignment 1 9 Sept. Programming in S 5 14 Sept. Exploratory Data Analysis using S-PLUS 16 Sept. More on S-PLUS Assignment 2 A 6 21 Sept. Introduction to LTEXand 23 Sept. related presentation tools 7 28 Sept. Interface between S and C/Fortran 30 Sept. More on Interface between S and C/Fortran Test 1 8 5 Oct. Random Numbers and 7 Oct. Monte Carlo Integration 9 12 Oct. Fall Break 14 Oct. Generating Discrete Random Variables 10 19 Oct. Generating Continuous Random Variables 21 Oct. More on generating random variables Assignment 3 11 26 Oct. Discrete Event Simulation Confirm Presentation Topic 28 Oct. Statistical Analysis of Simulated Data 12 2 Nov. Variance Reduction Techniques 4 Nov. Statistical Validation Techniques 13 9 Nov. Matrices and Linear Equations Assignment 4 11 Nov. Regression Computations 14 16 Nov. Optimization in Statistics 18 Nov. More on Optimization in Statistics Test 2 15 23 Nov. Resources on Internet 25 Nov. University Holiday – Thanksgiving 16 30 Nov. Student Presentations and Discussion

3 Textbooks:

Venables, W. N. and Ripley, B. D. (2002). Modern Applied Statistics with S-PLUS, 4th Edition. New York: Springer-Verlag.

Ross, S. M. (2002). Simulation, 3rd Edition. San Diego: Academic Press. References:

Devroye, L. (1986). Non-uniform Random Variate Generation. New York: Springer-Verlag.

Fishman, G. S. (1996). Monte Carlo: Concepts, Algorithms, and Applications. New York: Springer-Verlag.

Khuri, A. I. (1993). Advanced Calculus with Applications in Statistics. New York: John Wiley & Sons.

Lamport, L. (1994). LATEX: a document preparation system: user’s guide and reference manual, 2nd Edition. Reading, Massachusetts: Addison-Wesley Pub. Co.

Lange, K. (1999). Numerical Analysis for Statisticians. New York: Springer.

Maindonald, J. H. (1984). Statistical Computation. New York: John Wiley & Sons.

Maindonald, J. and Braun, J. (2003). Data Analysis and Graphics Using . United Kingdom: University Press, Cambridge.

Monahan, J. F. (2003). Numerical Methods of Statistics. United Kingdom: University Press, Cambridge.

Oetiker, T., Pertl, H., Hyna, I. and Schlegl, E. (2001). The Not so Short Introduction to LATEX2e, Version 3.20.

Robert, C. P. and Casella, G. (1999). Monte Carlo Statistical Methods. New York: Springer.

Tanner, M. A. (1996). Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions, 3rd Edition. New York: Springer-Verlag.

Thisted, R. A. (1988). Elements of Statistical Computing. New York: Chapman and Hall.

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