dswWienerCDF {WienR} | R Documentation |
Partial derivative of the first-passage time cumulative distribution function of the diffusion model with respect to the inter-trial variability of the relative starting point
Description
Calculates the partial derivative of the first-passage time cumulative distribution function of the diffusion model with respect to the inter-trial variability of the relative starting point sw.
Usage
dswWienerCDF(
t,
response,
a,
v,
w,
t0 = 0,
sv = 0,
sw,
st0 = 0,
precision = NULL,
K = NULL,
n.threads = FALSE,
n.evals = 6000
)
Arguments
t |
First-passage time. Numeric vector. |
response |
Response boundary. Character vector with |
a |
Upper barrier. Numeric vector. |
v |
Drift rate. Numeric vector. |
w |
Relative starting point. Numeric vector. |
t0 |
Non-decision time. Numeric vector |
sv |
Inter-trial variability of drift rate. Numeric vector. Standard deviation of a normal distribution |
sw |
Inter-trial variability of relative starting point. Numeric vector. Range of uniform distribution |
st0 |
Inter-trial variability of non-decision time. Numeric vector. Range of uniform distribution |
precision |
Optional numeric value. Precision of the partial derivative. Numeric value. Default is |
K |
Optional. Number of iterations to calculate the infinite sums. Numeric value (integer). Default is
We recommend using either default ( |
n.threads |
Optional numerical or logical value. Number of threads to use. If not provided (or 1 or |
n.evals |
Optional. Number of maximal function evaluations in the numeric integral. Default is |
Value
A list of the class Diffusion_deriv
containing
-
deriv
: the derivatives of the CDF with respect to w, -
call
: the function call, -
err
: the absolute error.
Author(s)
Raphael Hartmann
References
Hartmann, R., & Klauer, K. C. (2021). Partial derivatives for the first-passage time distribution in Wiener diffusion models. Journal of Mathematical Psychology, 103, 102550. doi:10.1016/j.jmp.2021.102550
Examples
dswWienerCDF(t = 1.2, response = "upper", a = 1.1, v = 13, w = .6, sw = .1)