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Stochastic models and their applications. Discrete and continuous-time jump Markov processes. A selection of topics from point processes, renewal theory, Markov decision processes, stochastic networks, inference for stochastic processes, simulation of stochastic processes, and computational methods using R.

Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.

Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.

Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.

Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.