[ 5MSSPKV ] KV Stochastic processes and modeling of time series
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| Es ist eine neuere Version 2021W dieser LV im Curriculum Master's programme Statistics and Data Science 2024W vorhanden. |
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| (*) Unfortunately this information is not available in english. |
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| Workload |
Education level |
Study areas |
Responsible person |
Hours per week |
Coordinating university |
| 4 ECTS |
M1 - Master's programme 1. year |
Statistics |
Milan Stehlik |
2 hpw |
Johannes Kepler University Linz |
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| Detailed information |
| Pre-requisites |
(*)keine
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| Original study plan |
Master's programme Statistics 2012W |
| Objectives |
Basic concepts of Stochastic Processes and Time Series.
Applications.
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| Subject |
1. Review of probability: Conditional probabilities and conditional expectations
2. Basic ideas about stochastic processes. Discrete and continuous state and discrete and continuous time stochastic processes. Markov chains and accompanying theory. Discrete-time Markov chains
3. Introduction to point processes, renewal processes
4. Exponential distribution and the Poisson process
5. MA, ARMA, ARIMA; GARCH
6. Introduction to simulation
7. Applications
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| Criteria for evaluation |
Exam, presentation of solved homeworks.
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| Methods |
Lecture, discussion of homeworks.
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| Language |
English |
| Study material |
Scriptum Helga Wagner: Stochastische Prozesse und Zeitreihenanalyse
N.T.J. Bailey, The elements of Stochastic Processes, Wiley, 1964
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| Changing subject? |
No |
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| On-site course |
| Maximum number of participants |
40 |
| Assignment procedure |
Assignment according to priority |
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