myStudy - Leuphana Universität Lüneburg

Dates

Curriculum context

Module

82007000 Forecasting and Prediction

Assessment

[29177] Forecasting and Prediction

Form of assessment

Written academic performance under supervision (90 Minutes)

Mode of performance

Handwritten in examination rooms at Leuphana

Examiner

Ulf Brefeld (responsible), Soham Majumder

Dates

Date of assessment: Thursday, 30.07.2026, 10:15, C HS 3
Resit date: : Keine selbständige Anmeldung zum Wiederholungstermin möglich.
Thursday, 17.09.2026, 10:15, C 14.027 Seminarraum

Notices

Anzeige von Anmeldebeginn und -ende systembedingt. Selbständige Anmeldung nur zum Prüfungstermin und nicht zum Wiederholungstermin möglich.

To the assessment in myCampus

Organizational information

Type of course

Lecture

planned way of execution

Vollständig Präsenz

Hours per week per semester

Registration process

centralized list procedure without participant limit

Maximum number of participants

Registration

Lottery procedure

centralized list procedure without participant limit

Time period

Registration ends 07.4.2026 at 23:59 h

Special features

If your registration for this course is successful you will registered automatically for the course Forecasting and Simulation - Ü (Ulf Brefeld, Soham Majumder).

Persons

Teaching staff

Ulf Brefeld

Soham Majumder

Content

Language of instruction

Englisch

Native Title

Forecasting and Simulation

Tags

Methodenorientiert - naturwissenschaftlich
Gasthörerprogramm

Content and concept

The module provides a survey of the theory and application of data-based computational techniques to forecast and simulate data with temporal dependencies. Selected statistical approaches dealing with the special role of time in modeling will be discussed in detail. Topics of interest include:
- stationary and non-stationary time series (ARIMA models)
- conditional heteroscedastic time series (ARCH and GARCH models)
- multivariate time series (VAR and VARMA models)
- state space models (Kalman Filter)

Objective

On successful completion of the module, students will have gained knowledge on selected methods of forecasting and simulating data with temporal dependencies and will be able to use these methods in various applications.

Other

If classroom teaching will not be possible, PowerPoint slides with added audio comments, R source code for practical tasks (as appropriate also with audio comments) and video conferencing with ZOOM are used to carry out the lectures.

Evaluation

This course has not been registered for teaching evaluation yet.

Further information on teaching evaluation: https://www.leuphana.de/en/teaching/quality-management/evaluation/course-evaluation.html