| CODE | SOR5501 | ||||||||||||
| TITLE | Computationally Intensive Methods | ||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||
| MQF LEVEL | 7 | ||||||||||||
| ECTS CREDITS | 10 | ||||||||||||
| DEPARTMENT | Statistics and Operations Research | ||||||||||||
| DESCRIPTION | Students taking this unit study-will be covering the topics which follow: - Monte Carlo Integration and Importance Sampling; - Jacknife and Bootstrap; - Variance Reduction; - Simulation of Stochastic Processes; - Optimisation using simulation; - MCMC Methods (Gibbs sampling, Metropolis Hastings algorithm); - Quasi Monte Carlo Methods; - Particle Filters/Sequential Monte Carlo Methods. Study-Unit Aims: To cover advanced computationally intensive methods, including a theoretical justification and some illustrative examples. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit, the student will be able to have the knowledge and understanding of the covered topics from a theoretical and practical perspective. 2. Skills: By the end of this study-unit, the student will be expected to be able to implement these techniques using standard programming languages such as R, Matlab or any other programming language of one's choice. Main Text/s and any supplementary readings: - Asmussen, S and Glynn, P. (2007). Stochastic Simulation: Algorithms and Analysis. Springer. - Brooks, S., Gelman, A., Jones, G.L. and Meng, X.L. (2011). Handbook of Markov Chain Monte Carlo. Chapman and Hall. - Carlin, B. P. and Louis, T. A. (2000). Bayes and Empirical Bayes Methods for Data Analysis. Chapman and Hall. - Gamerman, D. and Lopes, H. F. (2006). Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. - Chapman and Hall. Gentle, J.E. (2004) Random Number Generation and Monte Carlo Methods, Springer. - Gilks, W. R., Richardson, S. and Spiegelhalter, D.J. (1996). Markov Chain Monte Carlo in Practice. Springer-Science+Business Media. - Lemieux, C. (2009) Monte Carlo and Quasi-Monte Carlo Sampling. Springer. - Ripley, B. (2006) Stochastic Simulation. Wiley-Interscience. - Rubinstein, R. Y. and Kroese, D. P. (2008) Simulation and the Monte Carlo Method. Wiley. - Shao, J. and Dongsheng, T. (1996) The Jackknife and Bootstrap. Springer. |
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| STUDY-UNIT TYPE | Independent Study | ||||||||||||
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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