# NOT RUN {
p <- seq(0.01, 0.99, by = 0.01)
foldsqrtlink(p)
max(abs(foldsqrtlink(foldsqrtlink(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))
foldsqrtlink(p) # Has NAs
# }
# NOT RUN {
p <- seq(0.01, 0.99, by = 0.01)
par(mfrow = c(2, 2), lwd = (mylwd <- 2))
y <- seq(-4, 4, length = 100)
for (d in 0:1) {
matplot(p, cbind(logitlink(p, deriv = d), foldsqrtlink(p, deriv = d)),
type = "n", col = "purple", ylab = "transformation", las = 1,
main = if (d == 0) "Some probability link functions"
else "First derivative")
lines(p, logitlink(p, deriv = d), col = "limegreen")
lines(p, probitlink(p, deriv = d), col = "purple")
lines(p, clogloglink(p, deriv = d), col = "chocolate")
lines(p, foldsqrtlink(p, deriv = d), col = "tan")
if (d == 0) {
abline(v = 0.5, h = 0, lty = "dashed")
legend(0, 4.5, c("logitlink", "probitlink", "clogloglink", "foldsqrtlink"),
lwd = 2, col = c("limegreen", "purple", "chocolate", "tan"))
} else
abline(v = 0.5, lty = "dashed")
}
for (d in 0) {
matplot(y, cbind(logitlink(y, deriv = d, inverse = TRUE),
foldsqrtlink(y, deriv = d, inverse = TRUE)),
type = "n", col = "purple", xlab = "transformation", ylab = "p",
lwd = 2, las = 1,
main = if (d == 0) "Some inverse probability link functions"
else "First derivative")
lines(y, logitlink(y, deriv = d, inverse = TRUE), col = "limegreen")
lines(y, probitlink(y, deriv = d, inverse = TRUE), col = "purple")
lines(y, clogloglink(y, deriv = d, inverse = TRUE), col = "chocolate")
lines(y, foldsqrtlink(y, deriv = d, inverse = TRUE), col = "tan")
if (d == 0) {
abline(h = 0.5, v = 0, lty = "dashed")
legend(-4, 1, c("logitlink", "probitlink", "clogloglink", "foldsqrtlink"),
lwd = 2, col = c("limegreen", "purple", "chocolate", "tan"))
}
}
par(lwd = 1)
# }
# NOT RUN {
# This is lucky to converge
fit.h <- vglm(agaaus ~ sm.bs(altitude), binomialff(link = foldsqrtlink(mux = 5)),
data = hunua, trace = TRUE)
# }
# NOT RUN {
plotvgam(fit.h, se = TRUE, lcol = "orange", scol = "orange",
main = "Orange is Hunua, Blue is Waitakere")
# }
# NOT RUN {
head(predict(fit.h, hunua, type = "response"))
# }
# NOT RUN {
# The following fails.
pneumo <- transform(pneumo, let = log(exposure.time))
fit <- vglm(cbind(normal, mild, severe) ~ let,
cumulative(link = foldsqrtlink(mux = 10), par = TRUE, rev = TRUE),
data = pneumo, trace = TRUE, maxit = 200)
# }
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