Fitting (Exponential/Diffusion) RT-MPT Models R package rtmpt version 2.0-3 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). Software Depends: R (>= 3.5.0) Imports: coda, data.table, loo, methods, Ryacas, stats, stringr, truncnorm, utils Suggests: knitr, rmarkdown Raphael Hartmann <raphael.hartmann@protonmail.com> Comprehensive R Archive Network (CRAN) Raphael Hartmann [aut, cre], Karl C. Klauer [cph, aut, ctb, ths], Constantin G. Meyer-Grant [aut, ctb], Henrik Singmann [ctb, aut], Jean Marie Linhart [ctb], Frederick Novomestky [ctb] GPL (>= 2) 2025-03-19 application/tgz https://CRAN.R-project.org/package=rtmpt doi:10.32614/CRAN.package.rtmpt