Package: glba 0.2.1

glba: General Linear Ballistic Accumulator Models

Analyses response times and accuracies from psychological experiments with the linear ballistic accumulator (LBA) model from Brown and Heathcote (2008). The LBA model is optionally fitted with explanatory variables on the parameters such as the drift rate, the boundary and the starting point parameters. A log-link function on the linear predictors can be used to ensure that parameters remain positive when needed.

Authors:Ingmar Visser

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
glba/json (API)

# Install 'glba' in R:
install.packages('glba', repos = c('https://ingmarvisser.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • bh08 - Example data from Brown and Heathcote (2008).
  • ilpp2 - Implicit learning data from Visser et al (2007).
  • numpp1 - Example data from a numerosity task.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.05 score 1 stars 7 scripts 1.1k downloads 3 exports 0 dependencies

Last updated from:2e43a7bd8c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK103
source / vignettesOK203
linux-releaseOK92
macos-releaseOK98
macos-oldrelOK81
windows-develOK56
windows-releaseOK54
windows-oldrelOK55
wasm-releaseOK90

Exports:lbarlbatablba

Dependencies: