theta2theta | R Documentation |
Setting multiple process probabilities (thetas) equal. One of the process probabilities will be estimated and the other named process(es) will be set to equal the former. The equality can be removed by only using one name of a process.
theta2theta(model, names, keep_consts = FALSE)
set_thetas_equal(model, names, keep_consts = FALSE)
model |
A list of the class |
names |
Character vector giving the names of the processes for which the process probabilities should be equal. If
|
keep_consts |
Can be one of the following
|
A list of the class ertmpt_model
.
If you use theta2theta()
and tau2tau()
with the same process names you might just change the EQN or MDL file accordingly
by using the same process name for all processes which should have equal process times and probabilities.
Raphael Hartmann
delta2delta
, theta2const
, tau2zero
and tau2tau
####################################################################################
# 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 probabilities for both detection processes ("do" and "dn") will be
# set equal.
####################################################################################
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)
## make do = dn
new_model <- theta2theta(model = model, names = c("do", "dn"))
new_model
## make do = dn
new_model <- set_thetas_equal(model = model, names = c("do", "dn"))
new_model
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