Marginal.marginal_likelihood method that has
noise argument. It is
WhiteNoise covariance initialized with a scalar (variable). But what if i have measured uncertainties for each data point?
Latent implementation it is clear how to use the measured uncertainties.
Not sure I understand, the
noise argument in
gp.marginal_likelihood represents the uncertainties of the measurement. If you meant each data point has a different noise (so noise is a vector same size as observed) I think it should work by passing a vector to
It works with just setting
noise to an array of the measured uncertainties. Don’t know why this didn’t work earlier!