This package provides a unified interface for simulating and evaluating sequential sampling models (SSMs) in Julia. SSMs describe decision making as a stochastic and dynamic evidence accumulation process in which a decision is triggered by the option whose evidence hits a decision treshold first.
A summary of the core features is provided below. Please see the documentation for more information.
The following SSMs are supported:
The core API consists of the following
SSMs work with the following packages (and possibly more):
You can install a stable version of SequentialSamplingModels by running the following in the Julia REPL:
] add SequentialSamplingModels
In the example below, we instantiate a Linear Ballistic Accumulator (LBA) model, and generate data from it.
using SequentialSamplingModels
# Create LBA distribution with known parameters
dist = LBA(; ν=[2.75,1.75], A=0.8, k=0.5, τ=0.25)
# Sample 1000 random data points from this distribution
choice, rt = rand(dist, 1000)