Fit (exponential or diffusion) response-time extended multinomial processing tree (RT-MPT) models
by Klauer and Kellen (2018) and Klauer, Hartmann, and Meyer-Grant (submitted).
The RT-MPT class not only incorporate frequencies like traditional multinomial processing tree (MPT) models,
but also latencies. This enables it to estimate process completion times and encoding plus motor execution times
next to the process probabilities of traditional MPTs. 'rtmpt' is a hierarchical Bayesian framework and posterior
samples are sampled using a Metropolis-within-Gibbs sampler (for exponential RT-MPTs) or Hamiltonian-within-Gibbs
sampler (for diffusion RT-MPTs).