## written by Rick Dale (rdale@ucmerced.edu)
## build dichotomous simulated time-series data for testing
## Parameters to vary the mixing distribution of the simulated data
## values between 0,1.
# BL1 = rand*.5; % base event rate first conditional, confederate (driver)
# BL2 = .01; % base event rate first conditional, participant
# BLR1 = .33; % probability of repetition
# BLR2 = .33; % same, participant
# BL2C1 = .25; % probability of a match, third conditional
simts <- function(BL1,BL2,BLR1,BLR2,BL2C1,tsL) {
b1 = c(0)
b2 = c(0)
for (i in 1:(tsL-1)) {
if (runif(1) < BL1) {
b1 = c(b1,1)
}
else if (runif(1) < BLR1 & b1[length(b1)] == 1) {
b1 = c(b1,1)
}
else {
b1 = c(b1,0)
}
if (runif(1) < BL2C1 & b1[length(b1)-1] == 1) {
b2 = c(b2,1)
}
else if (runif(1) < BL2) {
b2 = c(b2,1)
}
else if (runif(1) < BLR2 & b2[length(b2)]==1) {
b2 = c(b2,1)
}
else {
b2 = c(b2,0)
}
}
return(rbind(b1,b2))
}
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