# On Model Selection in Cosmology

## TL;DR

This paper reviews various model selection methods in cosmology, comparing their premises and effectiveness, and advocates for the information theoretic approach as the most suitable for analyzing the Universe's expansion models.

## Contribution

It provides a comprehensive comparison of model selection techniques in cosmology and recommends the information theoretic approach as the most appropriate.

## Key findings

- Different model selection methods have distinct premises and objectives.
- The information theoretic approach is recommended for cosmological model comparison.
- The paper illustrates these methods using models of the Universe's expansion.

## Abstract

We review some of the common methods for model selection: the goodness of fit, the likelihood ratio test, Bayesian model selection using Bayes factors, and the classical as well as the Bayesian information theoretic approaches. We illustrate these different approaches by comparing models for the expansion history of the Universe. In the discussion we highlight the premises and objectives entering these different approaches to model selection and finally recommend the information theoretic approach.