passt

passt-package

<p>To run a simulation you will just need to use the function
<code><a rd-options="" href="/link/run_sim?package=passt&version=0.1.3" data-mini-rdoc="passt::run_sim">run_sim</a></code>, which will take care of the rest. To run
several simulations and get a standard analysis use the function
<code><a rd-options="" href="/link/run_exp?package=passt&version=0.1.3" data-mini-rdoc="passt::run_exp">run_exp</a></code>. Both functions take care of the details,
while you are still able to set the most important parameters such
as the learning rate development, the input patterns and the
independent variables of exposure frequency and exposure duration.</p>

internal

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.

Johannes Titz

Probability Associator Time (PASS-T)

passt-package function

<p>To run a simulation you will just need to use the function
<code><a rd-options='' href='run_sim'>run_sim</a></code>, which will take care of the rest. To run
several simulations and get a standard analysis use the function
<code><a rd-options='' href='run_exp'>run_exp</a></code>. Both functions take care of the details,
while you are still able to set the most important parameters such
as the learning rate development, the input patterns and the
independent variables of exposure frequency and exposure duration.</p>

passt-package: passt: Simulates judgments of frequency and duration with a competitive learning network based on the PASS-family

Description

Arguments

See Also