<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Computational modelling on Wise Lab Wiki</title><link>https://wiki.thewiselab.org/docs/computational_modelling/</link><description>Recent content in Computational modelling on Wise Lab Wiki</description><generator>Hugo</generator><language>en</language><copyright>Copyright (c) 2020-2024 Hyas</copyright><lastBuildDate>Mon, 01 Jan 0001 00:00:00 +0000</lastBuildDate><atom:link href="https://wiki.thewiselab.org/docs/computational_modelling/index.xml" rel="self" type="application/rss+xml"/><item><title>General best practices</title><link>https://wiki.thewiselab.org/docs/computational_modelling/general-best-practices/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://wiki.thewiselab.org/docs/computational_modelling/general-best-practices/</guid><description>Building models If possible, build models using JAX Make sure code is modular and well-documented Components that could be reused should be made into functions Contribute model code to behavioural_modelling if appropriate Fitting models See this paper for some useful advice on fitting models Model parameters should be estimated using a hierarchical Bayesian approach, with posterior samples obtained using MCMC MCMC should be run using Numpyro (unless this isn&amp;rsquo;t possible for any reason) Posteriors should be checked using traceplots and other diagnostics (e.</description></item></channel></rss>