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Prediction of time series

Course Code:
20Y2PR
Academic Degree:
master
Study Programme:
Technology in Transportation and Telecommunications (N 3710)
semesterlanguagestudy field / specialization
2czech flagall study fields
Transportation Systems and Technology (N1041A040003)
semesterlanguage
2czech flag
Logistics and Transport Processes Control (N1041A040005)
semesterlanguage
2czech flag
Form of Study:
full-time
Credits:
2
Number of Hours:
2 + 0 hours per week - in full-time study
Type of Course:
elective
Course Completion:
classified credit
Course Tutor:
 
roh  Lectures:
prof. Ing. Emil Pelikán, CSc.
Supervising Department:
Department of Transport Telematics (16120)
Keywords:
prediction, prediction of time series, regression models
Abstract:
Introduction to time series prediction, meaning of prediction, basics of quantitative prediction. Methods for predictive quality evaluation, descriptive statistics, MAE, MAPE, RMSE, naive prediction, prediction for general formula of loss function. Calculation and programming environment R. Regression models, basics of linear regression, simple regression. Multiple regression, statistical tests of linear dependence, selection of input variables.
Objectives:
The aim of the course is to acquaint students with the possibilities of prediction of time series, to teach students to understand the prediction quality evaluation and to create simple regression models.