EZ-CDM: easy estimation of circular diffusion model parameters
Recently, a circular diffusion model (CDM) (Smith, 2016) has been developed to handle both choices and response time for decisions in a continuous option space. It assumes that the process of evidence accumulation progresses following a Brownian motion within a circle and it terminates whenever the accumulator reaches any point on the perimeter, so a decision is made. While this model is excellent at capturing different continuous behavioral phenomena, it has not yet been welcomed and tested by decision psychologists due to its mathematical complexity. Here we propose a simple method for estimating the circular diffusion model parameters which only requires the calculation of straightforward formulas with some statistics of data. The method is based on the traditional method of moments. The accuracy in parameter recovery for the method is shown to be nearly the accuracy of the maximum likelihood method.