gld {fBasics} | R Documentation |
Generalized Lambda Distribution
Description
Density, distribution function, quantile function and random generation for the generalized lambda distribution.
Usage
dgld(x, lambda1 = 0, lambda2 = -1, lambda3 = -1/8, lambda4 = -1/8, log = FALSE)
pgld(q, lambda1 = 0, lambda2 = -1, lambda3 = -1/8, lambda4 = -1/8)
qgld(p, lambda1 = 0, lambda2 = -1, lambda3 = -1/8, lambda4 = -1/8)
rgld(n, lambda1 = 0, lambda2 = -1, lambda3 = -1/8, lambda4 = -1/8)
Arguments
lambda1 |
location parameter. |
lambda2 |
scale parameter. |
lambda3 |
first shape parameter. |
lambda4 |
second shape parameter. |
n |
number of observations. |
p |
a numeric vector of probabilities. |
x , q |
a numeric vector of quantiles. |
log |
a logical, if TRUE, probabilities |
Details
dgld
gives the density,
pgld
gives the distribution function,
qgld
gives the quantile function, and
rgld
generates random deviates.
Value
numeric vector
Author(s)
Chong Gu for code implemented from R's contributed package gld
.
Examples
## rgld -
set.seed(1953)
r = rgld(500,
lambda1=0, lambda2=-1, lambda3=-1/8, lambda4=-1/8)
plot(r, type = "l", col = "steelblue",
main = "gld: lambda1=0 lambda2=-1 lambda3/4=-1/8")
## dgld -
# Plot empirical density and compare with true density:
hist(r, n = 25, probability = TRUE, border = "white",
col = "steelblue")
x = seq(-5, 5, 0.25)
lines(x, dgld(x,
lambda1=0, lambda2=-1, lambda3=-1/8, lambda4=-1/8))
## pgld -
# Plot df and compare with true df:
plot(sort(r), ((1:500)-0.5)/500, main = "Probability",
col = "steelblue")
lines(x, pgld(x,
lambda1=0, lambda2=-1, lambda3=-1/8, lambda4=-1/8))
## qgld -
# Compute Quantiles:
qgld(pgld(seq(-5, 5, 1),
lambda1=0, lambda2=-1, lambda3=-1/8, lambda4=-1/8),
lambda1=0, lambda2=-1, lambda3=-1/8, lambda4=-1/8)
[Package fBasics version 4032.96 Index]