Mathematical Statistics II - Time Series Analysis
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
D01MSA2_EN | ZK | 2P | English |
- Course guarantor:
- Daniela Jarušková
- Lecturer:
- Daniela Jarušková
- Tutor:
- Supervisor:
- Department of Mathematics
- Synopsis:
-
Notion of time series. Stationary time series. Basic characteristics and their estimates. ARMA models. Frequency analysis of time series. Markovian sequences with finite number of states. Stationary distribution and method MCMC. Idea of MCMC for a continuous set of states.
- Requirements:
- Syllabus of lectures:
-
1.Notion of time series.
2. Stationary time series.
3. Basic characteristics and their estimates.
4. ARMA models. Frequency analysis of time series.
5.Markovian sequences with finite number of states.
6. Stationary distribution and method MCMC.
7. Idea of MCMC for a continuous set of states.
8. Aplication of MCMC method in Bayesian estimation.
- Syllabus of tutorials:
- Study Objective:
-
To get a knowledge how to model dependent variables. Knowledge methods for Baesian estimates.
- Study materials:
- Note:
- Time-table for winter semester 2024/2025:
- Time-table is not available yet
- Time-table for summer semester 2024/2025:
- Time-table is not available yet
- The course is a part of the following study plans: