This is a phd course in statistics - and requires active participation.

If you want to attend and have not received a zoom-link, then email andrea [dot] riebler [at] ntnu [dot] no.

Please help develop the course by answering this start-up quiz: https://tinyurl.com/y4zb5odp

Course coordinator/lecturer: Andrea Riebler

Course description: https://www.ntnu.edu/studies/courses/MA8702#tab=omEmnet

Course parts:

• Part 1: Markov chain Monte Carlo techniques with a link to the software Stan
• Part 2: Gaussian random fields and Integrated nested Laplace approximations
• Part 3: Sequential Monte Carlo Methods

Course evaluation:

The grade for this course is pass/fail, and 70/100 score is required to pass (this is the standard rule for PhD courses at NTNU).

Evaluation plan (pending approval by the IE faculty)

• Project 1 on part 1 (in group of size 2) [25%]
• Project 2 on part 2 (in group of size 2) [25%]
• Project 3 on part 3 (in group of size 2) [25%]
• Individual oral exam [25%]

There will also be some kind of obligatory participation in the presentation and discussion of research papers.

Recommended prerequisites:

• TMA4300 Computer-intensive statistical methods
• TMA4295 Statisticalinference
• TMA4267 Linear statistical models

Programming/IT-knowledge

Experience and good programming skills in R, or another high-level programming language.

• Håkon Gryvill, Email hakon.gryvill@ntnu.no
• Janne Cathrin Hetle Aspheim, Email janne.c.h.aspheim@ntnu.no