How do I find the min and max predicted probability of a hurdle model?

Question

Update: I used the following code:

 predict(h15, type = "zero")

When I do this the min=.2540 and max=136.9599 The max doesn't make sense because we are talking about probability. Can someone explain this to me please?

I need to find the min and max predicted probability of a hurdle model? I have provided my code and a picture of what I get. From here I am unsure how to find the min and max probability of having any derogatory marks against one’s credit, among those sampled.

 library(AER)
 cc <- CreditCard
 newcc <- cc[c(-79, -324, -435, -462, -656, -659, -1195),]
 h15 <- hurdle(reports ~ share + owner + active | share + owner +
            months + active , data = newcc, dist = "negbin")
 summary(h15)

Answer 1

"From here I am unsure how to find the min and max probability of having any derogatory marks against one’s credit, among those sampled."

So assuming the reports column in CreditCard records the number of derogatory remarks,

pred.matrix <- predict(h15, type = "prob")

produces a matrix (n rows X 15 columns) containing the probabilities of each possible outcome (0 - 14 in this case) for each of the n cases. The first column is the probability of 0 reports. So,

range(rowSums(pred.matrix[, -1]))
## [1] 0.00192127 0.71549271

produces the range (min and max) of the sum of the probabilities of an outcome > 0, for each case.