Quantifying the Bayesian Evidence for a Planet in Radial Velocity Data

Understand

We present results from a data challenge posed to the radial velocity (RV) community: namely, to quantify the Bayesian "evidence" for n={0,1,2,3} planets in a set of synthetically generated RV datasets containing a range of planet signals.

• Participating teams were provided the same likelihood function and set of priors to use in their analysis.
• They applied a variety of methods to estimate Z, the marginal likelihood for each n-planet model, including cross-validation, the Laplace approximation, importance sampling, and nested sampling.
• We found the dispersion in Z across different methods grew with increasing n-planet models: ~3 for 0-planets, ~10 for 1-planet, ~100-1000 for 2-planets, and >10,000 for 3-planets.