LBA: Hierarchical Linear Ballistic Accumulator model (Brown &...
In jeff324/powder: Power posterior sampling via differential evolution

Description Usage Format Value Fields Methods Examples

Hierarchical Linear Ballistic Accumulator model (Brown & Heathcote, 2008)

LBA

R6Class object.

Object of R6Class with methods for doing sampling with powder

theta.names

a character vector containing the names of the subject-level parameters

theta.init

a function that provides a random initial value for each subject-level parameter

theta.start.point

a numeric vector containing means of start points used to initialize in theta.init

phi.names

a character vector containing the names of the group-level parameters

phi.init

a function that initializes the group-level parameters

vary.parameter

a logical vector containing parameters to vary

prior

a list containing priors on all parameters

contaminant

a list specifying two values

pct: the percentage of the LBA distribution assumed to be due to random contaminants.
contaminant_bound: the upper bound of the contaminant distribution.

The contaminant distribution is assumed to be a uniform spanning from 0 to contaminant_bound.

log.dens.prior(x,hyper): likelihood of subject-level parameters given group-level parameters
log.dens.hyper(theta,phi,prior): summed log-likelihood for subject given group-level parameters and group given priors
log.dens.like(x,data,par.names): LBA likelihood function

## Not run: 
#LBA model that varies threshold across 3 conditions
model_threshold = LBA$new(b=T,conds=1:3)
#LBA model that varies correct drift rate over 2 conditions
model_drift = LBA$new(vc=T,conds=1:2)
#LBA model that varies start point variability and non-decision over 2 conditions
model_sp_t0 = LBA$new(t0=T,A=T,conds=1:2)

## End(Not run)