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.

Author
Ingmar Visser
Date of publication
2016-03-20 21:53:59
Maintainer
Ingmar Visser <i.visser@uva.nl>
License
GPL
Version
0.3

View on R-Forge

Man pages

bh08
Example data from Brown and Heathcote (2008).
core
Core functions to compute the probability density function,...
glba-package
Fit LBA models with explanatory variables.
ilpp2
Implicit learning data from Visser et al (2007).
internal
Utility functions for internal use.
lba
Specify and fit lba models.
numpp1
Example data from a numerosity task.
rlba
Generate data from an LBA model.
startlba
Specify and fit lba models.

Files in this package

glba/DESCRIPTION
glba/NAMESPACE
glba/NEWS
glba/R
glba/R/core.R
glba/R/internal.R
glba/R/lba.R
glba/R/rlba.R
glba/R/startlba.R
glba/data
glba/data/bh08.rda
glba/data/ilpp2.rda
glba/data/numpp1.rda
glba/man
glba/man/bh08.Rd
glba/man/core.Rd
glba/man/glba-package.Rd
glba/man/ilpp2.Rd
glba/man/internal.Rd
glba/man/lba.Rd
glba/man/numpp1.Rd
glba/man/rlba.Rd
glba/man/startlba.Rd