if there are censored data points, then the maximum-likelihood estimate (alpha, beta, sigsqr) is not valid

[Vladan1986]

Hello,

This is more of a question than an issue, but I am not clear about this sentence in the linmix documentation [https://linmix.readthedocs.io/en/latest/src/linmix.html], related to the delta parameter and the usage of the detection data with errors and limits:

delta (array_like) – Array indicating whether a data point is censored (i.e., not detected), or not. If delta[i] == 1, then the ith source is detected. If delta[i] == 0, then the ith source is not detected and y[i] will be interpreted as an upper limit. Note that if there are censored data points, then the maximum-likelihood estimate (alpha, beta, sigsqr) is not valid. By default, all data points are assumed to be detected.

It is not clear to me from the documentation how to have an access to the maximum likelihood value? Is this the mean of the posterior distribution of the parameters, e.g. :

print("{}, {}".format(lm.chain['alpha'].mean(), lm.chain['alpha'].std()))

print("{}, {}".format(lm.chain['beta'].mean(), lm.chain['beta'].std()))

or is it something else?

Thank you. Cheers,