NMAK13009U  Inference in Hidden Markov Models

Volume 2013/2014
MSc programme in Statistics
MSc programme in Actuarial Mathematics
MSc programme in Mathematics-Economics
Hidden Markov models: Definition and properties. Estimation by direct maximization of the likelihood, by the EM algorithm and further MC methods. Forecasting, decoding and prediction.
Learning Outcome
The student should know what Hidden markov models are and know about different inference methods.
The students shall be able to set up hidden Markov models, and obtain insight into accessible methods of parameter estimation, and apply them to relevant models.
The student should be able to generalize from the specific models introduced in the course to specific problems encountered further on.
Stok and Stat 1+2
2 + 2 hours of lectures and 2 hours of exercise sessions per week for 7 weeks.
7,5 ECTS
Type of assessment
Written assignment, 24 timer
Exam registration requirements
To pass the course, the student has to present exercises in class.
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
One internal examiner.
Same as ordinary exam
Criteria for exam assesment

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

  • Category
  • Hours
  • Lectures
  • 28
  • Practical exercises
  • 7
  • Preparation
  • 140
  • Exam
  • 24
  • Theory exercises
  • 7
  • Total
  • 206