Gaussian process regression gives better-calibrated uncertainties for hot Jupiter dayside temperatures than error-weighted averaging or linear interpolation, and produces a twelve-planet catalogue with credible error bars.
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Estimating dayside effective temperatures of hot Jupiters and associated uncertainties through Gaussian process regression
Gaussian process regression gives better-calibrated uncertainties for hot Jupiter dayside temperatures than error-weighted averaging or linear interpolation, and produces a twelve-planet catalogue with credible error bars.