```
# NOT RUN {
# Categorical regression example 1
pneumo <- transform(pneumo, let = log(exposure.time))
(fit1 <- vglm(cbind(normal, mild, severe) ~ let, propodds, data = pneumo))
fitted(fit1)
# LMS quantile regression example 2
fit2 <- vgam(BMI ~ s(age, df = c(4, 2)),
lms.bcn(zero = 1), data = bmi.nz, trace = TRUE)
head(predict(fit2, type = "response")) # Equal to the the following two:
head(fitted(fit2))
predict(fit2, type = "response", newdata = head(bmi.nz))
# Zero-inflated example 3
zdata <- data.frame(x2 = runif(nn <- 1000))
zdata <- transform(zdata, pstr0.3 = logit(-0.5 , inverse = TRUE),
lambda.3 = loglink(-0.5 + 2*x2, inverse = TRUE))
zdata <- transform(zdata, y1 = rzipois(nn, lambda = lambda.3, pstr0 = pstr0.3))
fit3 <- vglm(y1 ~ x2, zipoisson(zero = NULL), data = zdata, trace = TRUE)
head(fitted(fit3, type.fitted = "mean" )) # E(Y), which is the default
head(fitted(fit3, type.fitted = "pobs0")) # P(Y = 0)
head(fitted(fit3, type.fitted = "pstr0")) # Prob of a structural 0
head(fitted(fit3, type.fitted = "onempstr0")) # 1 - prob of a structural 0
# }
```

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