library(rstan)
library(RWiener)

.data <- rwiener(n = 80, alpha = 1.5, tau = .4, beta = .5, delta = 1)

.dstan <- list(
  N = nrow(.data), 
  rt = .data$q,
  resp = ifelse(.data$resp == "upper", 1, -1)
)

m1 <- stan_model("hmc_wfpt.stan")

fit1 <- sampling(m1, .dstan, chains = 1)