Mathematical Modelling

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Applied Mathematics

Synopsis:

Introduction to stochastic processes, basics of the queue theory, estimation of normal linear regression model and discrete model, general and Bayesian approach to the task of classification.

Requirements:

Basics of algebra, matrix calculus, differential and integral calculus. Knowledge of Probability and Statistics on a level of one year course in a technical university.

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

The goal is to proceede beyond the Probability and Statistics and give the students the basic knowledge in the field of stochastic processes and their use in some practical tasks. The basic element wil be a mathematical model of the stochastic process. On the basis of this model, several practical tasks will be solved.

Study materials:

1. I. Nagy, Základy bayesovského odhadování a řízení, Vydavatelství ČVUT, Praha, 2003.

2. Lukáš, L: Pravděpodobnostní modely v managementu, Markovovy řetězce a systémy hromadné obsluhy. Academia, 2009

3. M. Kárný, J. Böhm, T. V. Guy, L. Jirsa, I. Nagy, P. Nedoma, L. Tesař: Optimized Bayesian Dynamic Advising. Theory and algorithms. Springer, 2005

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: