dposnorm(x, mean = 0, sd = 1, log = FALSE)
pposnorm(q, mean = 0, sd = 1)
qposnorm(p, mean = 0, sd = 1)
rposnorm(n, mean = 0, sd = 1)
length(n) > 1
then the length is taken to be the number required.rnorm
.dposnorm
gives the density,
pposnorm
gives the distribution function,
qposnorm
gives the quantile function, and
rposnorm
generates random deviates.posnormal
, the posnormal
.m <- 0.8; x <- seq(-1, 4, len = 501)
plot(x, dposnorm(x, m = m), type = "l", ylim = 0:1, las = 1,
ylab = paste("posnorm(m = ", m, ", sd = 1)"), col = "blue",
main = "Blue is density, orange is cumulative distribution function",
sub = "Purple lines are the 10,20,...,90 percentiles")
lines(x, pposnorm(x, m = m), col = "orange")
abline(h = 0, col = "grey")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qposnorm(probs, m = m)
lines(Q, dposnorm(Q, m = m), col = "purple", lty = 3, type = "h")
lines(Q, pposnorm(Q, m = m), col = "purple", lty = 3, type = "h")
abline(h = probs, col = "purple", lty = 3)
max(abs(pposnorm(Q, m = m) - probs)) # Should be 0
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