MA8702 Advanced computer-intensive statistical methods - Spring 2024

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

Please help develop the course by answering this start-up quiz: https://forms.office.com/e/9sjC7xJ8k5

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, Integrated nested Laplace approximations, Model selection
• Part 3: Sequential Monte Carlo Methods

Course evaluation:

The grade for this course is pass/fail. There will be three projects, one for each lecture part, which need to be passed in order to be admitted to the exam.

There will also be required participation in the presentation and discussion of research papers.

Required previous knowledge:

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

Recommended previous knowledge:

• TMA4315 Generalized Linear Models

Programming/IT-knowledge

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

Reference group