STAT6079 Computer Intensive Statistical Methods
Aims and Objectives
To introduce and apply a number of recently developed statistical methods which require a large amount of computer power.
Having successfully completed this module you will be able to:
- Use IT skills developed by tackling computing problems through the use of a specific package (R).
- Demonstrate knowledge and understanding of the EM algorithm and extensions, and Markov chain Monte Carlo methods
- Use report writing and computing skills
- Write or modify S-Plus or R functions to implement these techniques and use them for model fitting or data analysis
- Demonstrate knowledge and understanding of the basic ideas of random number generation, re-sampling and simulation methods (bootstrap)
The following topics will be covered: basic concepts of programming, an introduction to R, random number generation, re-sampling and simulation methods (bootstrap), the EM algorithm and extensions, and Markov chain Monte Carlo methods.
Learning and Teaching
|Total study time||100|
Resources & Reading list
Other. There will be a blackboard site where all the module materials (slides, computer worksheets, assignments, list of books, etc.) will be made available. You will require access to R.
Robert, C. P. and Casella, G. (1999). Monte Carlo Statistical Methods.
Venables, W. N. and Ripley, B. D. (1996, 1997, 1999, 2002). Modern Applied Statistics with S(- Plus).
Venables, W. N. and Smith, D. M. (2002). An Introduction to R.
Davison, A. C. and Hinkley, D. V. (1997). Bootstrap Methods and their Application.
Tanner, M. A. (1991, 1993, 1996). Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions.
Gamerman, D. (1997). Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference.
Ripley, B. D. (1987). Stochastic Simulation.
Gilks, W. R., Richardson, S. and Spiegelhalter, D. J. (1996). Markov Chain Monte Carlo in Practice.
Little, R. and Rubin, D.B. (2001). Statistical Analysis with Missing Data (Chapter 8).
Efron, B. and Tibshirani, R. J. (1993). An Introduction to the Bootstrap.
Repeat type: Internal & External
To study this module, you will need to have studied the following module(s):
|STAT6083||Generalised Linear Models|