Stochastic Models and Their Applications

Lecturer:

Ivan Nagy (gar.)

Tutor:

Ivan Nagy (gar.)

Supervisor:

Department of Applied Mathematics

Synopsis:

This subject gives a preparation for introduction of the notions of stochastic model, its estimation and its use for prediction and control. It involves the basic elements from the theory of regression and state space modelling and the basic tasks connected with them. They are e.g. the state observation task and the pole assignment task. In the end, several specific examples, using the models introduced, will be listed. The applications will aim at the transportation area.

Requirements:

Basic knowledge from differential calculus and probability theory.

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

To give the basic knowledge about the dynamic systems, their modelling and their exploitation for the basic tasks of the systemtheory. Illustration of applications of modern methods in the process of analysis and decision making in transportation problems.

Study materials:

Statistical and Econometric Methods for Transportation Data Analysis Simon P. Washington , Matthew G. Karlaftis , Fred L. Mannering

Note:

Time-table for winter semester 2011/2012:

Time-table is not available yet

Time-table for summer semester 2011/2012:

Time-table is not available yet

The course is a part of the following study plans: