tef_applyWDM: Calculate the Wiener negative log likelihood of a vector of...

In akcochrane/TEfits: Time-evolving model fits

Calculate the Wiener negative log likelihood of a vector of data using a vector of drift rates.

Description

TEfit internal. Currently not supported. Within a TEfit call, errFun='wiener_df' is likely to be extremely slow, e.g., 70 seconds per run.

Usage

tef_applyWDM(dat, DR, BS, NDT, Bias = 0.5)

Arguments

dat	Vector of data (e.g., RT). Hitting upper bound must be positively signed; hitting lower bound must be negatively signed.
DR	Vector of drift rates. Must be the same length as dat.
BS	Boundary separation parameter. Positive scalar.
NDT	Non-decision time parameter. Positive scalar.
Bias	Bias parameter. Positive scalar.

Examples

dat <- c(-1,1,-.5,.5)
driftRate <- c(.2,.3,.4,.5)
tef_applyWDM(dat,DR=driftRate,BS=1,NDT=.3,Bias=.5)

akcochrane/TEfits documentation built on June 12, 2025, 11:10 a.m.