PřF:C7490 Intr. to Stochastic Modelling - Course Information

C7490 Introduction to Stochastic Modelling

Extent and Intensity

2/0/0. 3 credit(s). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).

Teacher(s)

prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)

Guaranteed by

prof. RNDr. Ladislav Dušek, Ph.D.
Chemistry Section – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D.

Prerequisites

Knowledge on basic unidimensional exploratory statistical techniques, analysis of variance, correlation analysis, simple regression.

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

• Analytical Chemistry (programme PřF, M-CH)
• Inorganic Chemistry (programme PřF, M-CH)
• Biochemistry (programme PřF, M-CH)
• Ecotoxicology (programme PřF, M-BI)
• Ecotoxicology (programme PřF, N-BI)
• Physical Chemistry (programme PřF, M-CH)
• Chemistry (programme PřF, M-CH)
• Environmental Chemistry (programme PřF, M-CH)
• Macromolecular Chemistry (programme PřF, M-CH)
• Organic Chemistry (programme PřF, M-CH)

Course objectives

Basic mathematical procedures with vectors and matrices, linear equations. Introduction to modelling.
Markov chains. Applications in modelling of succession of ecosystem, structure of biological populations.
Non - homogeneous Markov chains in ecology. Leslie matrix.
Simple applications of regression analysis.
Estimation of optimum of environmental parameters. Gaussian curves. Indicator species values.
Logistic regression - one- and multivariate model.
Multivariate linear regression. The least square method. The maximum likehood method.
Generalized multivariate linear model. Analysis of residuals - homoscedacity. Autocorrelation.
Role of correlation analysis in multivariate regression. Multicolinearity.
Nonlinear regression.
Modelling using contingency tables in ecology.
Introduction to time series analysis. Autocorrelation. Trend analysis. Non-parametric methods for estimation of trends.
Application of regression in trend analysis. Polynomial regression.
Box-Jwenkins modelling. Spline methods. Forecasting from time series.

Language of instruction

Czech

Further Comments

The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.

• Enrolment Statistics (Autumn 2001, recent)
  
• Permalink: https://is.muni.cz/course/sci/autumn2001/C7490