## compare type-I error rate for different recalibration types
types <- c("nominal", "golden", "controlled")
c <- seq(0.2, 5, by = 0.05)
t1 <- sapply(X = types, FUN = function(t) {
T1EpSceptical(type = t, c = c, alternative = "one.sided", level = 0.025)
})
matplot(
x = c, y = t1*100, type = "l", lty = 1, lwd = 2, las = 1, log = "x",
xlab = bquote(italic(c)), ylab = "Type-I error (%)",
xlim = c(0.2, 5)
)
legend("topright", legend = types, lty = 1, lwd = 2, col = seq_along(types))
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