This post is the second in the “Systemic Cookbook” series, which will show how to use Systemic 2 for scientific purposes (especially its more advanced features not readily accessible from its user interface). More comprehensive documentation for Systemic is forthcoming.
All posts in this series will be collected in the “Systemic 2″ category.
I wrote a short draft guide to doing Markov-Chain Monte Carlo-type of fitting and error analysis with Systemic2. This guide covers the very basics of the algorithm, the input parameters, and a step-by-step guide on how to drive the algorithm from the user interface, or from the C library. Please note that more sophisticated MCMC algorithms are available as R packages on CRAN.