Kumar {VGAM} | R Documentation |
Density, distribution function, quantile function and random generation for the Kumaraswamy distribution.
dkumar(x, shape1, shape2, log = FALSE)
pkumar(q, shape1, shape2, lower.tail = TRUE, log.p = FALSE)
qkumar(p, shape1, shape2, lower.tail = TRUE, log.p = FALSE)
rkumar(n, shape1, shape2)
x , q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations.
If |
shape1 , shape2 |
positive shape parameters. |
log |
Logical.
If |
lower.tail , log.p |
See kumar
, the VGAM family function
for estimating the parameters,
for the formula of the probability density function and other
details.
dkumar
gives the density,
pkumar
gives the distribution function,
qkumar
gives the quantile function, and
rkumar
generates random deviates.
T. W. Yee and Kai Huang
## Not run:
shape1 <- 2; shape2 <- 2; nn <- 201; # shape1 <- shape2 <- 0.5;
x <- seq(-0.05, 1.05, len = nn)
plot(x, dkumar(x, shape1, shape2), type = "l", las = 1,
ylab = paste("dkumar(shape1 = ", shape1,
", shape2 = ", shape2, ")"),
col = "blue", cex.main = 0.8, ylim = c(0,1.5),
main = "Blue is density, orange is the CDF",
sub = "Red lines are the 10,20,...,90 percentiles")
lines(x, pkumar(x, shape1, shape2), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qkumar(probs, shape1, shape2)
lines(Q, dkumar(Q, shape1, shape2), col = "red", lty = 3, type = "h")
lines(Q, pkumar(Q, shape1, shape2), col = "red", lty = 3, type = "h")
abline(h = probs, col = "red", lty = 3)
max(abs(pkumar(Q, shape1, shape2) - probs)) # Should be 0
## End(Not run)