ggdmc (version 0.2.5.2)

rlnr: Generate Random Choice RT Data from LNR Model

Description

Race among nacc accumulators, using log-normal race model

Usage

rlnr(n, meanlog, sdlog, t0, st0 = 0)

Arguments

n

numbers of observation

meanlog

a n_acc length vector or a n_acc x n matrix. mean of the distribution on the log scale without default value

sdlog

a n_acc length vector or a n_acc x n matrix. Standard deviation of the distribution on the log scale without default value.

t0

a scalar, a vector of length number of accumulators or a matrix with 1 row per accumulator, when start time differ on each trial

st0

range of non-decision time variability, must be a scalar, as the same variability is assumed in a common encoding/production stage

Value

a matrix

Examples

# NOT RUN {
## A simple demo
pmat <- matrix(c(-1, 0, 1, 1, .2, .2, 0, 0), 2)
set.seed(123)
dat0 <- rlnr(4, pmat[,1], pmat[,2], pmat[,3], pmat[1,4])
##           [,1] [,2]
## [1,] 0.4100361    0
## [2,] 0.4922407    0
## [3,] 1.7855260    1
## [4,] 0.4822220    1
##
## Three accumulators
n <- 1e5
meanlog <- c(.5, .75, 1);
sdlog <- c(1,1,1)
t0 <- c(.2,1,1)
set.seed(123)
dat1 <- rlnr(n, meanlog, sdlog, t0)
table(dat1[,2])
hist(dat1[,1], breaks = "fd", main = "", xlab ="")

## t0 has one element only
t0 <- .2
set.seed(123)
dat2 <- rlnr(n, meanlog, sdlog, t0)
table(dat2[,2])
hist(dat2[,1], breaks = "fd", freq = FALSE, main = "", xlab ="")
## check t0 noise
st0 <- 1
set.seed(123)
dat3 <- rlnr(n, meanlog, sdlog, t0, st0)
table(dat3[,2])
hist(dat3[,1], breaks = "fd", freq = FALSE, main = "", xlab ="")

# }