| tGPD | R Documentation | 
Density, distribution function, quantile function and random generation for the truncated Generalised Pareto Distribution (GPD).
dtgpd(x, gamma, mu = 0, sigma, endpoint = Inf, log = FALSE)
ptgpd(x, gamma, mu = 0, sigma, endpoint = Inf, lower.tail = TRUE, log.p = FALSE)
qtgpd(p, gamma, mu = 0, sigma, endpoint = Inf, lower.tail = TRUE, log.p = FALSE)
rtgpd(n, gamma, mu = 0, sigma, endpoint = Inf)
| x | Vector of quantiles. | 
| p | Vector of probabilities. | 
| n | Number of observations. | 
| gamma | The  | 
| mu | The  | 
| sigma | The  | 
| endpoint | Endpoint of the truncated GPD. 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  | 
The Cumulative Distribution Function (CDF) of the truncated GPD is equal to
F_T(x) = F(x) / F(T) for x \le T where F is the CDF of the ordinary GPD and T is the endpoint (truncation point) of the truncated GPD.
dtgpd gives the density function evaluated in x, ptgpd the CDF evaluated in x and qtgpd the quantile function evaluated in p. The length of the result is equal to the length of x or p.
rtgpd returns a random sample of length n.
Tom Reynkens
tGPD, Pareto, Distributions
# Plot of the PDF
x <- seq(0, 10, 0.01)
plot(x, dtgpd(x, gamma=1/2, sigma=5, endpoint=8), xlab="x", ylab="PDF", type="l")
# Plot of the CDF
x <- seq(0, 10, 0.01)
plot(x, ptgpd(x, gamma=1/2, sigma=5, endpoint=8), xlab="x", ylab="CDF", type="l")
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