p = seq(0.01, 0.99, by=0.01)
cauchit(p)
max(abs(cauchit(cauchit(p), inverse=TRUE) - p)) # Should be 0
p = c(seq(-0.02, 0.02, by=0.01), seq(0.97, 1.02, by=0.01))
cauchit(p) # Has no NAs
par(mfrow=c(2,2))
y = seq(-4, 4, length=100)
p = seq(0.01, 0.99, by=0.01)
for(d in 0:1) {
matplot(p, cbind(logit(p, deriv=d), probit(p, deriv=d)),
type="n", col="purple", ylab="transformation",
lwd=2, las=1, main = if (d == 0) "Some probability link functions"
else "First derivative")
lines(p, logit(p, deriv=d), col="limegreen", lwd=2)
lines(p, probit(p, deriv=d), col="purple", lwd=2)
lines(p, cloglog(p, deriv=d), col="chocolate", lwd=2)
lines(p, cauchit(p, deriv=d), col="tan", lwd=2)
if (d == 0) {
abline(v=0.5, h=0, lty="dashed")
legend(0, 4.5, c("logit", "probit", "cloglog", "cauchit"),
col=c("limegreen","purple","chocolate", "tan"), lwd=2)
} else
abline(v=0.5, lty="dashed")
}
for(d in 0) {
matplot(y, cbind(logit(y, deriv=d, inverse=TRUE),
probit(y, deriv=d, inverse=TRUE)),
type ="n", col="purple", xlab="transformation", ylab="p",
main = if (d == 0) "Some inverse probability link functions"
else "First derivative", lwd=2, las=1)
lines(y, logit(y, deriv=d, inverse=TRUE), col="limegreen", lwd=2)
lines(y, probit(y, deriv=d, inverse=TRUE), col="purple", lwd=2)
lines(y, cloglog(y, deriv=d, inverse=TRUE), col="chocolate", lwd=2)
lines(y, cauchit(y, deriv=d, inverse=TRUE), col="tan", lwd=2)
if (d == 0) {
abline(h=0.5, v=0, lty="dashed")
legend(-4, 1, c("logit", "probit", "cloglog", "cauchit"),
col=c("limegreen","purple","chocolate", "tan"), lwd=2)
}
}
Run the code above in your browser using DataLab