rtmpt
Fitting (Exponential/Diffusion) RT-MPT Models
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).
- Version2.0-2
- R versionR (≥ 3.5.0)
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- rtmpt citation info
- Last release01/23/2025
Documentation
Team
Raphael Hartmann
MaintainerShow author detailsKarl C. Klauer
Show author detailsRolesCopyright holder, Author, Contributor, Thesis advisorHenrik Singmann
Jean Marie Linhart
Show author detailsRolesContributorConstantin G. Meyer-Grant
Show author detailsRolesAuthor, ContributorFrederick Novomestky
Show author detailsRolesContributor
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- Imports6 packages
- Suggests2 packages