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Project 26: Comparing statistical models in practice - finding fast and good criteria

Suitable Majors

Applied Mathematics, Mathematics

Research Area

Bayesian statistical learning, Bayesian smoothing

Internship Description

The purpose of this project is to come up with suggestion about which model comparison criteria to use . 
Methodology: Simulation experiments, theoretical comparisons​

Prerequisites

Background in statistics and statistical computing, and/or machine learning.

Deliverables/Expectations

A set of recommendations for what model comparison criteria to use

Other Comments

​Internship dates: 7 July to 14 September​

Division

Computer, Electrical and Mathematical Sciences and Engineering

Faculty Name

Haavard Rue