Kursussøgning, efter- og videreuddannelse – Københavns Universitet

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Kursussøgning, efter- og videreuddannelse

Bayesian Statistics

Practical information
Study year 2016/2017
Time
Block 3
Programme level Ph.D.
ECTS 7,5 ECTS
Course responsible
  • Steffen L. Lauritzen (9-706579766d787e6972447165786c326f7932686f)
  • Department of Mathematical Sciences
Course number: NSCPHD1077

Course content

 

PLEASE NOTE         

The PhD course database is under construction. If you want to sign up for this course, please click on the link in order to be re-directed. Link: https://phdcourses.ku.dk/nat.aspx

 

  • 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

 

Recommended prerequisites

Basic understanding of mathematical statistics including conditional distributions

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Education

PhD programme in Statistics

Studyboard

Natural Sciences PhD Committee

Course type

Single subject courses (day)

Teacher

Steffen L. Lauritzen

Duration

1 block

Schedulegroup

A
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Teaching and learning methods

Lectures and theoretical exercises

Capacity

No restrictions/ no limitations

Language

English

Literature

C. P. Robert. The Bayesian Choice. 2nd edition. Springer-Verlag 2001. Paperback edition 2007.

Workload

Category Hours
Lectures 28
Theory exercises 18
Practical exercises 3
Exam 27
Preparation 130
English 206

Exam

Type of assessment

Written assignment, 27 hours
Written assignment

Aid

All aids allowed

Marking scale

7-point grading scale

Criteria for exam assessment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.

Censorship form

No external censorship

Re-exam

As for the ordinary exam

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