Markov Chain Monte Carlo with People (MCMCP)

Markov Chain Monte Carlo with People (MCMCP) is an adaptive procedure related to Gibbs Sampling with People (GSP). Like GSP, it is intended to map participants’ associations of a stimulus space. In each trial, the participant is presented with a pair of stimuli: a ‘current state’ and a ‘proposal state’. They are asked to decide which stimulus best matches a given criterion. The chosen stimulus is then accepted as the next state, and a new proposal is generated from that state by making a small random jump in the stimulus space.

Source: demos/mcmcp