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Construction, analysis and simulation of stochastic models, and optimisation problems associated with them. Poisson process, Markov chains, continuous-time Markov processes. Equilibrium distribution, reaching probabilities and times, transient behaviour. Use of R to simulate simple stochastic processes. Examples drawn from a range of applications including operations research, biology, and finance.

Construction, analysis and simulation of stochastic models, and optimisation problems associated with them. Poisson process, Markov chains, continuous-time Markov processes. Equilibrium distribution, reaching probabilities and times, transient behaviour. Use of R to simulate simple stochastic processes. Examples drawn from a range of applications including operations research, biology, and finance.

Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.

Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.

Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.

Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.