| Foldnorm {VGAM} | R Documentation |
Density, distribution function, quantile function and random generation for the (generalized) folded-normal distribution.
dfoldnorm(x, mean = 0, sd = 1, a1 = 1, a2 = 1, log = FALSE)
pfoldnorm(q, mean = 0, sd = 1, a1 = 1, a2 = 1,
lower.tail = TRUE, log.p = FALSE)
qfoldnorm(p, mean = 0, sd = 1, a1 = 1, a2 = 1,
lower.tail = TRUE, log.p = FALSE, ...)
rfoldnorm(n, mean = 0, sd = 1, a1 = 1, a2 = 1)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations.
Same as |
mean, sd |
see |
a1, a2 |
see |
log |
Logical.
If |
lower.tail, log.p |
|
... |
Arguments that can be passed into |
See foldnormal, the VGAM family function
for estimating the parameters,
for the formula of the probability density function and other details.
dfoldnorm gives the density,
pfoldnorm gives the distribution function,
qfoldnorm gives the quantile function, and
rfoldnorm generates random deviates.
T. W. Yee and Kai Huang.
Suggestions from Mauricio Romero led to improvements
in qfoldnorm().
## Not run:
m <- 1.5; SD <- exp(0)
x <- seq(-1, 4, len = 501)
plot(x, dfoldnorm(x, m = m, sd = SD), type = "l", ylim = 0:1, las = 1,
ylab = paste("foldnorm(m = ", m, ", sd = ",
round(SD, digits = 3), ")"),
main = "Blue is density, orange is cumulative distribution function",
sub = "Purple lines are the 10,20,...,90 percentiles", col = "blue")
abline(h = 0, col = "gray50")
lines(x, pfoldnorm(x, m = m, sd = SD), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qfoldnorm(probs, m = m, sd = SD)
lines(Q, dfoldnorm(Q, m, SD), col = "purple", lty = 3, type = "h")
lines(Q, pfoldnorm(Q, m, SD), col = "purple", lty = 3, type = "h")
abline(h = probs, col = "purple", lty = 3)
max(abs(pfoldnorm(Q, m = m, sd = SD) - probs)) # Should be 0
## End(Not run)