WienerPDF | R Documentation |
Calculate the first-passage time probability density function of the diffusion model.
WienerPDF(
t,
response,
a,
v,
w,
t0 = 0,
sv = 0,
sw = 0,
st0 = 0,
precision = NULL,
K = NULL,
n.threads = FALSE,
n.evals = 6000
)
dWDM(
t,
response,
a,
v,
w,
t0 = 0,
sv = 0,
sw = 0,
st0 = 0,
precision = NULL,
K = NULL,
n.threads = FALSE,
n.evals = 6000
)
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 PDF. 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 if sv, sw, and/or st0 are not zero. Default is |
A list of the class Diffusion_pdf
containing
pdf
: the PDF,
logpdf
: the log-transformed PDF,
call
: the function call,
err
: the absolute error. Only provided if sv, sw, or st0 is non-zero. If numerical integration is used, the precision cannot always be guaranteed.
Raphael Hartmann
Blurton, S. P., Kesselmeier, M., & Gondan, M. (2017). The first-passage time distribution for the diffusion model with variable drift. Journal of Mathematical Psychology, 76, 7–12. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jmp.2016.11.003")}
Foster, K., & Singmann, H. (2021). Another Approximation of the First-Passage Time Densities for the Ratcliff Diffusion Decision Model. arXiv preprint arXiv:2104.01902.
Gondan, M., Blurton, S. P., & Kesselmeier, M. (2014). Even faster and even more accurate first-passage time densities and distributions for the Wiener diffusion model. Journal of Mathematical Psychology, 60, 20–22. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jmp.2014.05.002")}
Hartmann, R., & Klauer, K. C. (2021). Partial derivatives for the first-passage time distribution in Wiener diffusion models. Journal of Mathematical Psychology, 103, 102550. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jmp.2021.102550")}
Navarro, D. J., & Fuss, I. G. (2009). Fast and accurate calculations for first-passage times in Wiener diffusion models. Journal of Mathematical Psychology, 53(4), 222–230. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jmp.2009.02.003")}
Wabersich, D., & Vandekerckhove, J. (2014). The RWiener Package: an R Package Providing Distribution Functions for the Wiener Diffusion Model. The R Journal, 6(1), 49. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.32614/rj-2014-005")}
WienerPDF(t = 1.2, response = "upper", a = 1.1, v = 13, w = .6, precision = NULL, K = NULL)
dWDM(t = 1.2, response = "upper", a = 1.1, v = 13, w = .6, precision = NULL, K = NULL)
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