Description Usage Arguments Value References Examples
Density function and random generation for the circular drift-diffusion
model with theta vector equal to pVec
. dcddm
is the
equation (23) on page 433 in Smith (2016).
1 2 3 |
x |
a matrix storing a first column as RT and a second column of continuous responses/reports/outcomes. Each row is a trial. |
pVec |
a parameter vector with the order [a, vx, vy, t0, s], or [thresh, mu1, mu2, ndt, sigmasq]. The order matters. |
k |
a precision for calculating the infinite series in |
n |
number of observations. |
p |
a precision for random walk step in |
dcddm
gives a log-likelihood vector. rddm
generates
random deviates, returning a n x 3 matrix with the columns: RTs, choices
and then angles.
Smith, P. L. (2016). Diffusion Theory of Decision Making in Continuous Report, Psychological Review, 123 (4), 425–451.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## dcddm example
x <- cbind(
RT= c(1.2595272, 0.8693937, 0.8009044, 1.0018933, 2.3640007, 1.0521304),
R = c(1.9217430, 1.7844653, 0.2662521, 2.1569724, 1.7277440, 0.8607271)
)
pVec <- c(a=2.45, vx=1.5, vy=1.25, t0=.1, s=1)
dcddm(x, pVec)
## rcddm example
pVec <- c(a=2, vx=1.5, vy=1.25, t0=.25, s=1)
den <- rcddm(1e3, pVec);
hist(den[,1], breaks = "fd", xlab="Response Time", main="Density")
hist(den[,3], breaks = "fd", xlab="Response Angle", main="Density")
|
[,1]
[1,] -1.7925136
[2,] -0.9038642
[3,] 1.1758415
[4,] -2.6084263
[5,] -3.2489231
[6,] 1.5580843
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