mrpy.fitting.fit_sample.SimFit.lnL¶
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SimFit.
lnL
(p, ret_jac=False, debug=0)¶ Return the log-likelihood of the current model at the parameters p.
Parameters: p : array
The values of the parameters,
[logHs, alpha, beta]
.ret_jac : bool
Whether to return the jacobian as the second arg.
debug : int, optional
Set the level of info printed out throughout the function. Highest current level that is useful is 2.
Returns: ll : float
The log-likelihood at the parameters. This is exactly the same as used in the fitting process.
jac : length-3 array, optional
Returned only if ret_jac is True. The jacobian at the current parameter vector.