This is an old version, view current version.

17.1 General configuration

All of the optimizers have the option of including the the log absolute Jacobian determinant of inverse parameter transforms in the log probability computation. Without the Jacobian adjustment, optimization returns the maximum likelihood estimate (MLE), \(\mathrm{argmax}_{\theta}\ p(y | \theta)\), the value which maximizes the likelihood of the data given the parameters. Applying the Jacobian adjustment produces the maximum a posteriori estimate (MAP), that maximizes the value of the posterior density in the unconstrained space, \(\mathrm{argmax}_{\theta}\ p(y | \theta)\,p(\theta)\).

All of the optimizers are iterative and allow the maximum number of iterations to be specified; the default maximum number of iterations is 2000.

All of the optimizers are able to stream intermediate output reporting on their progress. Whether or not to save the intermediate iterations and stream progress is configurable.