dnaka(x, shape, scale = 1, log = FALSE)
pnaka(q, shape, scale = 1)
qnaka(p, shape, scale = 1, ...)
rnaka(n, shape, scale = 1, Smallno = 1.0e-6)
nakagami
for more details.
For rnaka
, arguments shape
and scale
must be of
length 1.pnaka(U) > 1-Smallno
where U
is the upper limit.uniroot
.log = TRUE
then the logarithm of the density is returned.dnaka
gives the density,
pnaka
gives the cumulative distribution function,
qnaka
gives the quantile function, and
rnaka
generates random deviates.nakagami
for more details.nakagami
.x <- seq(0, 3.2, len = 200)
plot(x, dgamma(x, shape = 1), type = "n", col = "black", ylab = "",
ylim = c(0,1.5), main = "dnaka(x, shape)")
lines(x, dnaka(x, shape = 1), col = "orange")
lines(x, dnaka(x, shape = 2), col = "blue")
lines(x, dnaka(x, shape = 3), col = "green")
legend(2, 1.0, col = c("orange","blue","green"), lty = rep(1, len = 3),
legend = paste("shape =", c(1, 2, 3)))
plot(x, pnorm(x), type = "n", col = "black", ylab = "",
ylim = 0:1, main = "pnaka(x, shape)")
lines(x, pnaka(x, shape = 1), col = "orange")
lines(x, pnaka(x, shape = 2), col = "blue")
lines(x, pnaka(x, shape = 3), col = "green")
legend(2, 0.6, col = c("orange","blue","green"), lty = rep(1, len = 3),
legend = paste("shape =", c(1, 2, 3)))
probs <- seq(0.1, 0.9, by = 0.1)
pnaka(qnaka(p = probs, shape = 2), shape = 2) - probs # Should be all 0
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