Lecturer

Dr. Pavel Grabarnik, Russian Academy of Sciences

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Time and place

Lecture
Tuesday, 12–14 h, He 22, Room 202/ 203

Homework session
Thursday, 12-13 h, He 22, Room 202/ 203

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Class

4 weeks, beginning Tuesday, November 20

Lecture: 2 h/week

Homework session: 1 h/week

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Prerequisites

Probability Calculus (required), Statistics (recommended)

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Intended audience

Students and Ph.D. students with interest in stochastics

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Content

Markov chains represent one of the basic statistical models for sequences of random variables, which exhibit a certain dependence structure. There exist various applications, amongst others, in finance and insurance, but also, for example, in life and biosciences. Besides, one often faces with a problem that the mathematical model becomes so complex that explicit analytic formulae do not exist. In this case, Markov chain Monte Carlo simulation is used as an auxiliary tool to obtain approximate solutions.

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Further information

This lecture is held within the framework of the activities of the DFG Research Training Group "Modelling, analysis and simulation in economy mathematics" at the Ulm University.

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