SequentialSamplingModels.jl

Documentation is under construction.

This package is a collection of sequential sampling models and is based on the Distributions.jl API. Sequential sampling models, also known as an evidence accumulation models, are a broad class of dynamic models of human decision making in which evidence for each option accumulates until the evidence for one option reaches a decision threshold. Models within this class make different assumptions about the nature of the evidence accumulation process. See the references below for a broad overview of sequential sampling models. An example of the evidence accumulation process is illustrated below for the leaking competing accumulator.

lca_plot

Installation

You can install a stable version of SequentialSamplingModels by running the following in the Julia REPL:

] add SequentialSamplingModels

The package can then be loaded with:

using SequentialSamplingModels

References

Evans, N. J. & Wagenmakers, E.-J. Evidence accumulation models: Current limitations and future directions. Quantitative Methods for Psychololgy 16, 73–90 (2020).

Forstmann, B. U., Ratcliff, R., & Wagenmakers, E. J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. Annual Review of Psychology, 67, 641-666.

Jones, M., & Dzhafarov, E. N. (2014). Unfalsifiability and mutual translatability of major modeling schemes for choice reaction time. Psychological Review, 121(1), 1.