dCSTM_TW_grid: Generate Grid for PDF of Custom Time- and Weight-Dependent...
In ream: Density, Distribution, and Sampling Functions for Evidence Accumulation Models
dCSTM_TW_grid R Documentation
Generate Grid for PDF of Custom Time- and Weight-Dependent Drift Diffusion Model
Description
Beschreibung.
Usage
dCSTM_TW_grid(rt_max = 10, phi, x_res = "default", t_res = "default")
Arguments
rt_max
maximal response time <- max(rt)
phi
parameter vector in your order
x_res
spatial/evidence resolution
t_res
time resolution
Value
such and such
Author(s)
Raphael Hartmann & Matthew Murrow
References
Murrow, M., & Holmes, W. R. (2023). PyBEAM: A Bayesian approach to parameter inference for a wide class of binary evidence accumulation models.
Behavior Research Methods.
ream documentation built on Oct. 7, 2024, 1:20 a.m.
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| dCSTM_TW_grid | R Documentation |
Generate Grid for PDF of Custom Time- and Weight-Dependent Drift Diffusion Model
Description
Beschreibung.
Usage
dCSTM_TW_grid(rt_max = 10, phi, x_res = "default", t_res = "default")
Arguments
rt_max |
maximal response time <- max(rt) |
phi |
parameter vector in your order |
x_res |
spatial/evidence resolution |
t_res |
time resolution |
Value
such and such
Author(s)
Raphael Hartmann & Matthew Murrow
References
Murrow, M., & Holmes, W. R. (2023). PyBEAM: A Bayesian approach to parameter inference for a wide class of binary evidence accumulation models. Behavior Research Methods.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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