# NOT RUN {
polf("p", cutpoint = 2, short = FALSE)
polf("p", cutpoint = 2, tag = TRUE)
p <- seq(0.01, 0.99, by = 0.01)
y <- polf(p, cutpoint = 2)
y. <- polf(p, cutpoint = 2, deriv = 1)
max(abs(polf(y, cutpoint = 2, inv = TRUE) - p)) # Should be 0
#\ dontrun{ par(mfrow = c(2, 1), las = 1)
#plot(p, y, type = "l", col = "blue", main = "polf()")
#abline(h = 0, v = 0.5, col = "orange", lty = "dashed")
#
#plot(p, y., type = "l", col = "blue",
# main = "(Reciprocal of) first POLF derivative")
#}
# Rutherford and Geiger data
ruge <- data.frame(yy = rep(0:14,
times = c(57,203,383,525,532,408,273,139,45,27,10,4,0,1,1)))
with(ruge, length(yy)) # 2608 1/8-minute intervals
cutpoint <- 5
ruge <- transform(ruge, yy01 = ifelse(yy <= cutpoint, 0, 1))
fit <- vglm(yy01 ~ 1, binomialff(link = polf(cutpoint = cutpoint)), ruge)
coef(fit, matrix = TRUE)
exp(coef(fit))
# Another example
pdata <- data.frame(x2 = sort(runif(nn <- 1000)))
pdata <- transform(pdata, x3 = runif(nn))
pdata <- transform(pdata, mymu = exp( 3 + 1 * x2 - 2 * x3))
pdata <- transform(pdata, y1 = rpois(nn, lambda = mymu))
cutpoints <- c(-Inf, 10, 20, Inf)
pdata <- transform(pdata, cuty = Cut(y1, breaks = cutpoints))
#\ dontrun{ with(pdata, plot(x2, x3, col = cuty, pch = as.character(cuty))) }
with(pdata, table(cuty) / sum(table(cuty)))
fit <- vglm(cuty ~ x2 + x3, data = pdata, trace = TRUE,
cumulative(reverse = TRUE,
parallel = TRUE,
link = polf(cutpoint = cutpoints[2:3]),
multiple.responses = TRUE))
head(depvar(fit))
head(fitted(fit))
head(predict(fit))
coef(fit)
coef(fit, matrix = TRUE)
constraints(fit)
fit@misc$earg
# }
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