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Table C.1

p-value of the K-S statistic for all marginalised posterior distributions from retrievals of scattered instances of SP-TW.

log10(pKS)
Rp CO2 CO H2O CH4 H2S SO2 HCN C2H2 pcloud Tp0 Tp1 Tp2 Tp3
0 −45.1 −76.0 −138.9 −144.0 −59.4 −1.5 −16.9 −23.5 −10.3
1 −40.0 −75.5 −141.2 −145.4 −55.0 −1.9 −16.9 −24.5 −9.6
2 −41.3 −77.8 −141.1 −140.3 −51.5 −1.5 −17.1 −25.0 −9.8
3 −41.4 −76.0 −142.0 −141.0 −54.0 −2.7 −16.2 −22.6 −10.0
4 −44.1 −78.1 −140.2 −142.2 −57.2 −2.2 −16.1 −24.1 −10.3
5 −42.6 −75.1 −141.5 −144.1 −52.9 −1.7 −20.1 −23.3 −10.5
6 −43.0 −75.2 −141.0 −143.3 −53.6 −1.7 −18.9 −24.2 −9.7
7 −43.7 −76.6 −140.5 −140.7 −54.9 −1.5 −19.3 −23.1 −10.4
8 −39.2 −74.7 −140.7 −144.5 −54.4 −1.2 −20.4 −22.1 −10.3
9 −43.1 −77.3 −144.2 −139.6 −54.3 −1.8 −16.6 −22.4 −10.4

Notes. Two-sample K-S statistics are calculated between the marginalised posteriors of the original instance of SP-TW and of the scattered instances for each parameter. We have used the resample_equal() method as implemented in the nestle Python package to resample the samples to have equal weights1. Values reported in the table are the base-10 logarithm of the p-value associated with the K-S statistic, where empty entries correspond to values of pKS = 0.

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