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Fit (exponential or diffusion) response-time extended multinomial processing tree (RT-MPT) models by Klauer and Kellen (2018) doi:10.1016/j.jmp.2017.12.003 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).
Citation | rtmpt citation info |
System requirements | GSL (>=2.3) |
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