ST227 Half Unit
This information is for the 2012/13 session.
Primarily for students on the following programmes: BSc Actuarial Science, BSc Business Mathematics and Statistics. Also available to General Course students and as an outside option.
Pre-requisites: MA100 Mathematical Methods, ST102 Elementary Statistical Theory.
An introduction to stochastic processes with emphasis on life history analysis and actuarial applications.
Principles of modelling; model selection, calibration, and testing; Stochastic processes and their classification into different types by time space, state space, and distributional properties; construction of stochastic processes from finite-dimensional distributions, processes with independent increments, Poisson processes and renewal processes and their applications in general insurance and risk theory, Markov processes, Markov chains and their applications in life insurance and general insurance, extensions to more general intensity-driven processes, counting processes, semi-Markov processes, stationary distributions. Determining transition probabilities and other conditional probabilities and expected values; Integral expressions, Kolmogorov differential equations, numerical solutions, simulation techniques. Survival models - the random life length approach and the Markov chain approach; survival function, conditional survival function, mortality intensity, some commonly used mortality laws. Statistical inference for life history data; Maximum likelihood estimation for parametric models, non-parametric methods (Kaplan-Meier and Nelson-Aalen), regression models for intensities including the semi-parametric Cox model and partial likelihood estimation; Various forms of censoring; The technique of occurrence-exposure rates and analytic graduation; Impact of the censoring scheme on the distribution of the estimators; Confidence regions and hypothesis testing.
Lectures: 20 LT.
Seminars: 10 LT.
Compulsory written answers to two sets of problems.
Three-hour written examination in the ST.