STK4190 – Bayesian nonparametrics
Statistical analysis involves first setting up a model for data in terms of certain unknown parameters. Bayesian analysis proceeds by placing a prior distribution on these parameters and then deriving and using relevant aspects of the consequent posterior distribution. Bayesian nonparametrics is the extended branch of such modelling and analyses where the parameter of the model is of very high or infinite dimension, as when one models an unknown density, regression, or link function. This calls for more complex mathematics and computational schemes than for the classical cases where the parameter is of low dimension. There are links to and implications for machine learning.
After having completed the course you will have learned some of the more prominent nonparametric prior constructions and ensuing posterior calcuations:
- the Dirichlet process;
- the Beta process;
- Gaussian processes;
- bigger hierarchical models;
- applications with real data.
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Recommended previous knowledge
and one of the following courses:
STK2100 – Machine Learning and Statistical Methods for Prediction and Classification
STK2120 – Statistical Methods and Data Analysis 2 (discontinued)
STK3100 – Introduction to Generalized Linear Models
10 credits overlap with STK9190 – Bayesian nonparametrics
3 hours of lectures/exercises per week.
Depending on the number of students, the exam will be in one of the following four forms:
1. Only written exam
2. Only oral exam
3. A project paper followed by a written exam.
4. A project paper followed by an oral exam/hearing.
For the latter two the project paper and the exam counts equally and the final grade is based on a general impression after the final exam. (The two parts of the exam will not be individually graded.)
The form of examination will be announced by the teaching staff by 15 October/15 March for the autumn semester and the spring semester respectively.
Examination support material
No examination support material is allowed.
Language of examination
Subjects taught in English will only offer the exam paper in English.
You may write your examination paper in Norwegian, Swedish, Danish or English.
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.
Explanations and appeals
Resit an examination
This course offers both postponed and resit of examination. Read more:
Withdrawal from an examination
It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.
Special examination arrangements
Application form, deadline and requirements for special examination arrangements.
The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation.