dPL | R Documentation |
Density, distribution function, quantile function,
random generation and hazard function for the Power Lindley distribution
with parameters mu
and sigma
.
dPL(x, mu, sigma, log = FALSE)
pPL(q, mu, sigma, lower.tail = TRUE, log.p = FALSE)
qPL(p, mu, sigma, lower.tail = TRUE, log.p = FALSE)
rPL(n, mu, sigma)
hPL(x, mu, sigma)
x , q |
vector of quantiles. |
mu |
parameter. |
sigma |
parameter. |
log , log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
p |
vector of probabilities. |
n |
number of observations. |
The Power Lindley Distribution with parameters mu
and sigma
has density given by
f(x) = \frac{\mu \sigma^2}{\sigma + 1} (1 + x^\mu) x ^ {\mu - 1} \exp({-\sigma x ^\mu}),
for x > 0.
dPL
gives the density, pPL
gives the distribution
function, qPL
gives the quantile function, rPL
generates random deviates and hPL
gives the hazard function.
Amylkar Urrea Montoya, amylkar.urrea@udea.edu.co
almalki2014modificationsRelDists
\insertRefGhitanya2013RelDists
old_par <- par(mfrow = c(1, 1)) # save previous graphical parameters
## The probability density function
curve(dPL(x, mu=1.5, sigma=0.2), from=0.1, to=10,
col="red", las=1, ylab="f(x)")
## The cumulative distribution and the Reliability function
par(mfrow=c(1, 2))
curve(pPL(x, mu=1.5, sigma=0.2),
from=0.1, to=10, col="red", las=1, ylab="F(x)")
curve(pPL(x, mu=1.5, sigma=0.2, lower.tail=FALSE),
from=0.1, to=10, col="red", las=1, ylab="R(x)")
## The quantile function
p <- seq(from=0, to=0.99999, length.out=100)
plot(x=qPL(p, mu=1.5, sigma=0.2), y=p, xlab="Quantile",
las=1, ylab="Probability")
curve(pPL(x, mu=1.5, sigma=0.2), from=0.1, add=TRUE, col="red")
## The random function
hist(rPL(n=1000, mu=1.5, sigma=0.2), freq=FALSE,
xlab="x", las=1, main="")
curve(dPL(x, mu=1.5, sigma=0.2), from=0.1, to=15, add=TRUE, col="red")
## The Hazard function
par(mfrow=c(1,1))
curve(hPL(x, mu=1.5, sigma=0.2), from=0.1, to=15,
col="red", ylab="Hazard function", las=1)
par(old_par) # restore previous graphical parameters
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