Mathematical Statistics II
The course is not on the list Without time-table
| Code | Completion | Credits | Range | Language |
|---|---|---|---|---|
| D01MS2_EN | ZK | 2P | English |
- Course guarantor:
- Lecturer:
- Tutor:
- Supervisor:
- Department of Mathematics
- Synopsis:
-
Multivariate normal distribution. Principal component analysis. Linear regression. Nonlinear regression. Bayes theorem. Bayesian parameters estimates. Bayesian inference in linear model. Time series and their frequency domain description. Kalman-Bucy filtr.
.
- Requirements:
-
Basic statistical course of statistics either in their MGr studies or in the course Mathematical statistics I.
- Syllabus of lectures:
- Syllabus of tutorials:
- Study Objective:
-
To get a deeper knowledge that is of interest for students, especially for their future disertation thesis.
- Study materials:
-
Jay Devore: Probability and Statistics for Engineering and the Sciences.
Larry Wasserman: All of Statistics. A concise Course in Statistical Inference, Springer, 2005.
- Note:
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: