Course - Advanced Modern Statistical Methods - MA8702
MA8702 - Advanced Modern Statistical Methods
About
Examination arrangement
Examination arrangement: Portfolio assessment
Grade: Passed/Failed
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Arbeider | 30/100 | |||
| Muntlig eksamen | 70/100 |
Course content
This subject is normally taught every second year, next
time spring 2016. A condition is that sufficiently many students are registered.
The course will give a theoretical and methodological
introduction and discussion of modern statistical methods, but assumes also good computational skills. Topics to be discussed are a selection of the following; theory and methods for Markov chain Monte Carlo, Hidden Markov chains, Gaussian Markov random fields, mixtures, non-parametric methods and regression, splines, bootstrapping, classification and graphical models, latent Gaussian models and their approximate Bayesian inference. Relative weighting of the various topics will vary according to need.
Learning outcome
1. Knowledge.
The course will give a theoretical and methodological introduction and discussion of modern statistical methods, but assumes also good computational skills. Topics to be discussed are a selection of the following; theory and methods for Markov chain Monte Carlo, Hidden Markov chains, Gaussian Markov random fields, mixtures, non-parametric methods and regression, splines, bootstrapping, classification and graphical models, latent Gaussian models and their approximate Bayesian inference.
2. Skills.
The students should learn and be able to use the basic techniques in the modern theoretical statistics. In particular, Markov chain, Monte Carlo, Hidden Markov chains, Gaussian Markov random fields, mixtures, non-parametric methods and regression, splines, bootstrapping, classification and graphical models, latent Gaussian models and their approximate Bayesian inference.
3. Competence.
The students should be able to participate in scientific discussions and conduct researches in statistics on high international level. They should be able to participate in applied projects involving statistical methods and apply their knowledge in problems in theoretical statistics.
Learning methods and activities
Lectures, alternatively guided self-study.
Compulsory assignments
- Exercises
Recommended previous knowledge
This subject is a continuation of TMA4300 Modern
statistics methods and TMA4295 Statistical Inference, TMA4267 Linear statistical models.
Course materials
Will be announced at the start of the course.
Version: 1
Credits:
7.5 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: SPRING 2016
Language of instruction: -
-
- Statistics
Department with academic responsibility
Department of Mathematical Sciences
Examination
Examination arrangement: Portfolio assessment
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD Arbeider 30/100
-
Room Building Number of candidates - Autumn ORD Muntlig eksamen 70/100
-
Room Building Number of candidates - Spring ORD Arbeider 30/100
-
Room Building Number of candidates - Spring ORD Muntlig eksamen 70/100
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"