A course in stochastic modeling is lectured (in English) at the Mathematical Department (Åbo Akademi University) starting on Monday 12th of Jamuary at 10.15 in room Hilbertrummet (ASA, Fänriksgatan 3 B, 3rd floor).

Lecturing hours:

• Mon 10-12, Hilbertrummet
• Wed 13-15, Hilbertrummet
• Fri 10-12, Hilbertrummet

Aim is to give an introduction to the mathematical theory of stochastic processes and their use in a variety of applications.

Contents: The following are the main topics discussed on the course:

• Discrete time Markov chains
• Poisson and counting processes
• Continuous time Markov chains

The mathematical theory is illustrated by analyzing and modeling data from some real world phenomenon extracted from Guttorp’s book (the first reference below). Topics like Hidden Markov models, Markov Chain Monte Carlo methods, Renewal theory and Queueuing models are also shortly presented as the time schedule so allows.

Lectures are based on the following literature:

• Guttorp, P.: Stochastic Modeling of Scientific Data (1st ed. 1995. 2nd ed, 2014). Chapman & Hall/CRC,
• Ross, S. M.: Introduction to Probability Models (10th ed. 2010, 11th ed. 2014). Academic Press.

Prerequisities: mathematical analysis (second year calculus), probability theory (a second year course).

Lecturer/contact: Paavo Salminen, e-mail:phsalmin@abo.fi

A course in stochastic modeling is lectured (in English) at the Mathematical Department (Åbo Akademi University) starting on Monday 12th of Jamuary at 10.15 in room Hilbertrummet (ASA, Fänriksgatan 3 B, 3rd floor).

Lecturing hours:

• Mon 10-12, Hilbertrummet
• Wed 13-15, Hilbertrummet
• Fri 10-12, Hilbertrummet

Aim is to give an introduction to the mathematical theory of stochastic processes and their use in a variety of applications.

Contents: The following are the main topics discussed on the course:

• Discrete time Markov chains
• Poisson and counting processes
• Continuous time Markov chains

The mathematical theory is illustrated by analyzing and modeling data from some real world phenomenon extracted from Guttorp’s book (the first reference below). Topics like Hidden Markov models, Markov Chain Monte Carlo methods, Renewal theory and Queueuing models are also shortly presented as the time schedule so allows.

Lectures are based on the following literature:

• Guttorp, P.: Stochastic Modeling of Scientific Data (1st ed. 1995. 2nd ed, 2014). Chapman & Hall/CRC,
• Ross, S. M.: Introduction to Probability Models (10th ed. 2010, 11th ed. 2014). Academic Press.

Prerequisities: mathematical analysis (second year calculus), probability theory (a second year course).

Lecturer/contact: Paavo Salminen, e-mail:phsalmin@abo.fi