tau2zero: Set process completion times to zero

In rtmpt: Fitting (Exponential/Diffusion) RT-MPT Models

Set process completion times to zero

Description

Setting process completion times (taus) to zero or change it back to be estimated.

Usage

tau2zero(model, names, outcomes, values = 0)

set_tau_zero(model, names, outcomes, values = 0)

Arguments

model	A list of the class ertmpt_model.
names	Character vector with process names.
outcomes	Character vector of length length(names) indicating for which process outcome the process completion time should be zero or changed back to be estimated. Allowed characters are: "minus": the negative outcome of the process. "plus": the positive outcome of the process.
values	Numerical vector of length one or length(names). You have the following options for the elements of the numeric vector: 0: suppress the process time/rate, i.e., set the process completion time (tau) with the specified output to zero. NA: estimate the process time (tau)

Value

A list of the class ertmpt_model.

Author(s)

Raphael Hartmann

See Also

delta2delta, theta2const, theta2theta and tau2tau

Examples

####################################################################################
# Detect-Guess variant of the Two-High Threshold model.
# The encoding and motor execution times are assumed to be equal for each category.
# The process completion times for both failed detections will be suppressed.
####################################################################################

mdl_2HTM <- "
# targets
do+(1-do)*g
(1-do)*(1-g)

# lures
(1-dn)*g
dn+(1-dn)*(1-g)

# do: detect old; dn: detect new; g: guess
"

model <- to_ertmpt_model(mdl_file = mdl_2HTM)

## removing the process times (tau) for the failed (="minus") detection ("do" and "dn") 
new_model <- tau2zero(model = model, names = c("dn", "do"),
                      outcomes = c("minus", "minus"), values = 0)
new_model


## removing the process times (tau) for the failed (="minus") detection ("do" and "dn") 
new_model <- set_tau_zero(model = model, names = c("dn", "do"),
                          outcomes = c("minus", "minus"), values = 0)
new_model

rtmpt documentation built on April 4, 2025, 12:37 a.m.