# NOT RUN {
nbolf("p", cutpoint = 2, k = 1, short = FALSE)
nbolf("p", cutpoint = 2, k = 1, tag = TRUE)
p <- seq(0.02, 0.98, by = 0.01)
y <- nbolf(p,cutpoint = 2, k = 1)
y. <- nbolf(p,cutpoint = 2, k = 1, deriv = 1)
max(abs(nbolf(y,cutpoint = 2, k = 1, inv = TRUE) - p)) # Should be 0
#\ dontrun{ par(mfrow = c(2, 1), las = 1)
#plot(p, y, type = "l", col = "blue", main = "nbolf()")
#abline(h = 0, v = 0.5, col = "red", lty = "dashed")
#
#plot(p, y., type = "l", col = "blue",
# main = "(Reciprocal of) first NBOLF derivative") }
# Another example
nn <- 1000
x2 <- sort(runif(nn))
x3 <- runif(nn)
mymu <- exp( 3 + 1 * x2 - 2 * x3)
k <- 4
y1 <- rnbinom(nn, mu = mymu, size = k)
cutpoints <- c(-Inf, 10, 20, Inf)
cuty <- Cut(y1, breaks = cutpoints)
#\ dontrun{ plot(x2, x3, col = cuty, pch = as.character(cuty)) }
table(cuty) / sum(table(cuty))
fit <- vglm(cuty ~ x2 + x3, trace = TRUE,
cumulative(reverse = TRUE, multiple.responses = TRUE,
parallel = TRUE,
link = nbolf(cutpoint = cutpoints[2:3], k = k)))
head(depvar(fit))
head(fitted(fit))
head(predict(fit))
coef(fit)
coef(fit, matrix = TRUE)
constraints(fit)
fit@misc
# }
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