Is your feature request related to a problem? Please describe.
The CCP method related to #449 would require to correct the optimised values for each new X_n+1, considering a bound M, to have the expected theoretical guarantees .
Describe the solution you'd like
We need to re-optimize the g function, with an augmented dataset composed by the n calibration points and X_n+1. It can still be interesting to compute the optimisation with only the n calibration points, to use this optimised value as starting value for the inference optimizations.
Is your feature request related to a problem? Please describe. The CCP method related to #449 would require to correct the optimised values for each new X_n+1, considering a bound M, to have the expected theoretical guarantees .
Describe the solution you'd like We need to re-optimize the g function, with an augmented dataset composed by the n calibration points and X_n+1. It can still be interesting to compute the optimisation with only the n calibration points, to use this optimised value as starting value for the inference optimizations.