PROSPECT: A profile likelihood code for frequentist cosmological parameter inference

Understand

Cosmological parameter inference has been dominated by the Bayesian approach for the past two decades, primarily due to its computational efficiency.

• However, the Bayesian approach involves integration of the posterior probability and therefore depends on both the choice of model parametrisation and the choice of prior on the model parameter space.
• In some cases, this can lead to conclusions which are driven by choice of parametrisation and priors rather than by data.
• The profile likelihood method provides a complementary frequentist tool which can be used to investigate this effect.