ThGaskin / NeuralABM

Neural parameter calibration for multi-agent models. Uses neural networks to estimate marginal densities on parameters and networks
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Improvements to marginal calculations #41

Closed ThGaskin closed 9 months ago

ThGaskin commented 11 months ago

:warning: Major commit :warning: Breaking change

Overview

This PR represents a major overhaul of the marginal calculation for all models. In place of the current implementation, the joint density with the likelihood is calculated first. The marginals are then obtained by integrating over this 2-dimensional joint density. Normalisation and integrals are calculated using scipy.integrate functions. This leads to a significantly improved prediction accuracy and a theoretically well-supported computationally procedure. Prior distributions are now enforced in all models.

Other changes:

Can this PR be accepted?