On Likelihood FittingΒΆ
The LogLikelihood
objective function should be
used to perform log-likelihood maximization. The
__call__()
and eval_jacobian()
definitions have
been changed to facilitate what one would expect from Likelihood fitting:
__call__ gives the value of log-likelihood at the given values of \(\vec{p}\) and \(\vec{x}_i\), where \(\vec{p}\) is a shorthand notation for all parameter, and \(\vec{x}_i\) the same shorthand for all independent variables.
eval_jacobian()
gives the derivative
with respect to every parameter of the log-likelihood:
Where \(\nabla_{\vec{p}}\) is the derivative with respect to all parameters
\(\vec{p}\). The function therefore returns a vector of length len(p)
containing the Jacobian evaluated at the given values of \(\vec{p}\) and
\(\vec{x}\).