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Table 4

Bayesian model comparison for the RV data.

Model Priors (d) Posteriors (d) ln 𝒵 ∆ ln 𝒵 max. log likelihood
0P + dSHO(96d) 𝒩Prot,GP(96, 6) 94.9273 −397.7 −15.0 −378.4
1P(36 d-ecc) + dSHO(96 d) 𝒰b(30, 40) 36.1234 −388.7 −6.0 −351.6
𝒩Prot,GP(96, 6) 103.1397
1P(36 d-circ) + dSHO(96 d) 𝒰b(30, 40) 36.1185 −388.6 −5.9 −355.4
𝒩Prot,GP(96, 6) 101.1691
2P(36 d-ecc, 113 d-ecc) + dSHO(96 d) 𝒰b(30, 40) 36.1154 −387.1 −4.4 −344.0
𝒰c(100, 120) 113.4702
𝒩Prot,GP(96, 6) 98.3681
2P(36 d-circ, 113 d-ecc) + dSHO(96 d) 𝒰b(30, 40) 36.1234 −384.5 −1.8 −341.6
𝒰c(100, 120) 113.4132
𝒩Prot,GP(96, 6) 98.3081
2P(36 d-circ, 113 d-circ) + dSHO(96 d) 𝒰b(30, 40) 36.1173 −382.9 −0.2 −344.1
𝒰c(100, 120) 113.4677
𝒩Prot,GP(96, 6) 99.2176
2P(36 d-ecc, 113 d-circ) + dSHO(96 d) 𝒰b(30, 40) 36.1186 −382.7 0.0 −341.9
𝒰c(100, 120) 113.4634
𝒩Prot,GP(96, 6) 97.6017

Notes. The model used for the final fit is the 2P(36d-ecc, 113d-circ) + dSHO-GP(96d) model highlighted in boldface. Wide, unconstrained priors are denoted as “blind”.

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