MA8702 Advanced computer-intensive statistical methods - Spring 2022

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

  • 17.01.2022: The lecture on Wednesday 19.01 will be via Zoom, using the same link as last week. The lecture on the 26.01 as well as the paper discussion are planned to be physical.
  • 09.01.2022: The teaching of the course starts on January 12, 10:15-12:00, via zoom. If you want to attend and have not received a zoom-link, then email andrea [dot] riebler [at] ntnu [dot] no. In the first two weeks of the semester the teaching will be digital, if the corona restrictions defined by NTNU allow teaching will be physical afterwards.

Please help develop the course by answering this start-up quiz: https://tinyurl.com/bdcu883m

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. 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 some kind of obligatory 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

2022-01-17, Andrea Riebler