Παρουσίαση/Προβολή

The course aims to develop a broad and thorough working knowledge of modern computational statistics, to enable use of modern statistical methods in practice. In more complex situations this will mean using optimisation routines to obtain maximum likelihood estimates for the parameters and estimates of uncertainty. The course also considers how to evaluate such stochastic models, how to generate random variables and the use of simulation. Outline syllabus includes: Function optimisation. Advanced likelihood tools. Fundamental features of modelling. Model selection. Generating random variables. Simulation techniques and Monte Carlo. Resampling methods.