NSCPHD1077 Bayesian Statistics
Volume 2016/2017
Education
PhD programme in Statistics
Content
PLEASE NOTE
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- The Bayesian paradigm
- Sufficiency and likelihood
- Prior and posterior distributions
- Decision theoretic foundations
- Conjugate prior distributions
- Default prior distributions
- Bayesian parameter estimation
- Bayesian computation
- Bayes factors and model choice
- Bayesian asymptotics
- Empirical Bayes methods
Learning Outcome
Knowledge:
Basic knowledge of the topics covered
Skills:
- Discuss and understand basics of the Bayesian paradigm
- Understand how decision theory underpins Bayesian inference
- Understand methods for constructing prior distributions
- Discuss and understand basic principles for Bayesian model choice
Competences:
- Ability to use standard software for simple modelling and Bayesian computation
- Ability to construct and perform a Bayesian analysis of statistical models
Literature
C. P. Robert. The Bayesian Choice. 2nd edition. Springer-Verlag 2001. Paperback edition 2007.
Recommended Academic Qualifications
Basic understanding of
mathematical statistics including conditional
distributions
Teaching and learning methods
Lectures and theoretical
exercises
Workload
- Category
- Hours
- Exam
- 27
- Lectures
- 28
- Practical exercises
- 3
- Preparation
- 130
- Theory exercises
- 18
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignment, 27 hoursWritten assignment
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
- Re-exam
As for the ordinary exam
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Course information
- Language
- English
- Course code
- NSCPHD1077
- Credit
- 7,5 ECTS
- Level
- Ph.D.
- Duration
- 1 block
- Placement
- Block 3
- Schedule
- A
- Course capacity
- No restrictions/ no limitations
- Continuing and further education
- Study board
- Natural Sciences PhD Committee
Contracting department
- Department of Mathematical Sciences
Course responsibles
- Steffen L. Lauritzen (9-6e6377746b767c6770426f63766a306d7730666d)
Lecturers
Steffen L. Lauritzen
Saved on the
22-03-2016