Introduction:The selection of the “best” model typically involves both objective (numerical) and subjective criteria, such as interpretation of plots and consideration of biological plausibility. Multi Objective Optimization (MOO) allows for the simultaneous optimization of multiple criteria. This approach generates a Pareto front, representing a set of non-dominated models where no single solution can be improved […]
Author: marksale
ADPO: Automatic-differentiation-assisted parametric optimization algorithm
Objectives: Compare two alternative approaches to parameter estimation using the first-order conditional estimation with interaction (FOCE-I) method in mixed-effect non-linear regression for efficiency and robustness. Methods: Typically, in the FOCE-I, finite difference (FD) is used to approximate the gradient. FD is a numerical approximation to the gradient, accomplished by calculating the objective function value at […]
PyDarwin Designer, a prototype, user friendly interface to pyDarwin for machine learning based model selection.
pyDarwin(1) is a Python package with a command line API, designed for machine learning model selection in NONMEM and NLME. It doesn’t have a graphical user interface (GUI). Instead, it requires users to manually create three files: a template file, a tokens file, and an options file. The tokens and options files are formatted in […]