tBurr {ReIns} | R Documentation |
The truncated Burr distribution
Description
Density, distribution function, quantile function and random generation for the truncated Burr distribution (type XII).
Usage
dtburr(x, alpha, rho, eta = 1, endpoint = Inf, log = FALSE)
ptburr(x, alpha, rho, eta = 1, endpoint = Inf, lower.tail = TRUE, log.p = FALSE)
qtburr(p, alpha, rho, eta = 1, endpoint = Inf, lower.tail = TRUE, log.p = FALSE)
rtburr(n, alpha, rho, eta = 1, endpoint = Inf)
Arguments
x |
Vector of quantiles. |
p |
Vector of probabilities. |
n |
Number of observations. |
alpha |
The |
rho |
The |
eta |
The |
endpoint |
Endpoint of the truncated Burr distribution. The default value is |
log |
Logical indicating if the densities are given as |
lower.tail |
Logical indicating if the probabilities are of the form |
log.p |
Logical indicating if the probabilities are given as |
Details
The Cumulative Distribution Function (CDF) of the truncated Burr distribution is equal to
F_T(x) = F(x) / F(T)
for x \le T
where F
is the CDF of the ordinary Burr distribution and T
is the endpoint (truncation point) of the truncated Burr distribution.
Value
dtburr
gives the density function evaluated in x
, ptburr
the CDF evaluated in x
and qtburr
the quantile function evaluated in p
. The length of the result is equal to the length of x
or p
.
rtburr
returns a random sample of length n
.
Author(s)
Tom Reynkens.
See Also
Examples
# Plot of the PDF
x <- seq(0, 10, 0.01)
plot(x, dtburr(x, alpha=2, rho=-1, endpoint=9), xlab="x", ylab="PDF", type="l")
# Plot of the CDF
x <- seq(0, 10, 0.01)
plot(x, ptburr(x, alpha=2, rho=-1, endpoint=9), xlab="x", ylab="CDF", type="l")