pastas.solver.mcmc.Emcee.log_likelihood#

pastas.solver.mcmc.Emcee.log_likelihood(p: pastas.typing.ArrayLike, noise: bool, weights: pandas.Series | None = None, callback: pastas.typing.CallBack | None = None) → float#

Log-likelihood function.

Parameters:

  • p (numpy.Array) – Numpy array with the parameters.

  • noise (bool) – If True, the noise model is applied to the residuals. This is passed on to the misfit function, which will apply the noise model if True.

  • weights (pandas.Series, optional) – Series with weights for the residuals. This is passed on to the misfit function, which will apply the weights if provided.

  • callback (callable, optional) – Callback function that will be called after each iteration of the solver. This is passed on to the misfit function, which will call the callback if provided.

Returns:

lnlike – The log-likelihood for the parameters.

Return type:

float

Notes

This method is always called by emcee.