Closed Jammy2211 closed 2 months ago
Methods which found the maximum likelihood model were previously called optimize, which this PR renames to MLE (maximum likelihood estimator).
optimize
This PR improves the MLE methods with functionality including:
Initializer
The BFGS and LBFGS MLE searches have been improved in this PR, including visualization.
BFGS
LBFGS
The main use case is fits where a good starting point is known and simple gradient descent can find the maximum likelihood solution.
The intent is to use this for strong lens sensitivity mapping.
The bulk of functionality is included in the following autofit PR:
https://github.com/rhayes777/PyAutoFit/pull/1029
Methods which found the maximum likelihood model were previously called
optimize, which this PR renames to MLE (maximum likelihood estimator).This PR improves the MLE methods with functionality including:
InitializerAPI.The
BFGSandLBFGSMLE searches have been improved in this PR, including visualization.The main use case is fits where a good starting point is known and simple gradient descent can find the maximum likelihood solution.
The intent is to use this for strong lens sensitivity mapping.
The bulk of functionality is included in the following autofit PR:
https://github.com/rhayes777/PyAutoFit/pull/1029