New preprint on estimating and comparing models with time-varying parameters

Hello there,

we just published a new preprint on the validation and comparison of non-stationary diffusion decision models:

We used BayesFlow for parameter estimation and model comparison. Code and data can be found in our bayesflow-org on GitHub: Non-Stationary-DDM-Validation

Any feedback or comment is welcomed.

ps. A tutorial notebook on the development and estimation of non-stationary cognitive models within a superstatistics framework is coming soon.