passt: Probability Associator Time (PASS-T)
Simulates judgments of frequency and duration based on
    the Probability Associator Time (PASS-T) model. PASS-T is a memory
    model based on a simple competitive artificial neural network. It 
    can imitate human judgments of frequency and duration, which have
    been extensively studied in cognitive psychology
    (e.g. Hintzman (1970) <doi:10.1037/h0028865>, Betsch et al. (2010)
    <https://psycnet.apa.org/record/2010-18204-003>). The PASS-T model
    is an extension of the PASS model (Sedlmeier, 2002,
    ISBN:0198508638). The package provides an easy way to run
    simulations, which can then be compared with empirical data in
    human judgments of frequency and duration.
| Version: | 0.1.3 | 
| Imports: | magrittr, methods, dplyr, tidyr, rlang | 
| Suggests: | knitr, ggplot2, plyr, testthat (≥ 2.1.0), covr, markdown, rmarkdown | 
| Published: | 2021-05-03 | 
| DOI: | 10.32614/CRAN.package.passt | 
| Author: | Johannes Titz [aut, cre] | 
| Maintainer: | Johannes Titz  <johannes.titz at gmail.com> | 
| BugReports: | https://github.com/johannes-titz/passt/issues | 
| License: | GPL-3 | 
| URL: | https://github.com/johannes-titz/passt | 
| NeedsCompilation: | no | 
| Materials: | NEWS | 
| CRAN checks: | passt results | 
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