Package: passt 0.1.3

Johannes Titz

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.

Authors:Johannes Titz [aut, cre]

passt_0.1.3.tar.gz
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passt.pdf |passt.html
passt/json (API)
NEWS

# Install 'passt' in R:
install.packages('passt', repos = c('https://johannes-titz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/johannes-titz/passt/issues

On CRAN:

3.70 score 3 scripts 154 downloads 3 exports 21 dependencies

Last updated 4 years agofrom:d2d3482b64. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-winOKNov 03 2024
R-4.5-linuxOKNov 03 2024
R-4.4-winOKNov 03 2024
R-4.4-macOKNov 03 2024
R-4.3-winOKNov 03 2024
R-4.3-macOKNov 03 2024

Exports:%>%run_exprun_sim

Dependencies:clicpp11dplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr

A too short introduction to PASS-T with the passt R package

Rendered frompasst.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2019-10-31
Started: 2019-10-21