Density, distribution function, quantile function,
random generation and hazard function for the Cosine Sine Exponential distribution
with parameters mu
, sigma
and nu
.
Usage
dCS2e(x, mu, sigma, nu, log = FALSE)
pCS2e(q, mu, sigma, nu, lower.tail = TRUE, log.p = FALSE)
qCS2e(p, mu, sigma, nu, lower.tail = TRUE, log.p = FALSE)
rCS2e(n, mu, sigma, nu)
hCS2e(x, mu, sigma, nu)
Value
dCS2e
gives the density, pCS2e
gives the distribution
function, qCS2e
gives the quantile function, rCS2e
generates random deviates and hCS2e
gives the hazard function.
Details
The Cosine Sine Exponential Distribution with parameters mu
,
sigma
and nu
has density given by
\(f(x)=\frac{\pi \sigma \mu \exp(\frac{-x} {\nu})}{2 \nu [(\mu\sin(\frac{\pi}{2} \exp(\frac{-x} {\nu})) + \sigma\cos(\frac{\pi}{2} \exp(\frac{-x} {\nu}))]^2}, \)
for \(x > 0\), \(\mu > 0\), \(\sigma > 0\) and \(\nu > 0\).
References
Chesneau C, Bakouch HS, Hussain T (2018). “A new class of probability distributions via cosine and sine functions with applications.” Communications in Statistics-Simulation and Computation, 1–14.
Examples
old_par <- par(mfrow = c(1, 1)) # save previous graphical parameters
## The probability density function
par(mfrow=c(1,1))
curve(dCS2e(x, mu=1, sigma=0.1, nu =0.1), from=0, to=1,
ylim=c(0, 3), col="red", las=1, ylab="f(x)")
## The cumulative distribution and the Reliability function
par(mfrow=c(1, 2))
curve(pCS2e(x, mu=1, sigma=0.1, nu =0.1),
from=0, to=1, col="red", las=1, ylab="F(x)")
curve(pCS2e(x, mu=1, sigma=0.1, nu =0.1, lower.tail=FALSE),
from=0, to=1, col="red", las=1, ylab="R(x)")
## The quantile function
p <- seq(from=0, to=0.99999, length.out=100)
plot(x=qCS2e(p, mu=0.1, sigma=1, nu=0.1), y=p, xlab="Quantile",
las=1, ylab="Probability")
curve(pCS2e(x, mu=0.1, sigma=1, nu=0.1), from=0, add=TRUE, col="red")
## The random function
hist(rCS2e(n=10000, mu=0.1, sigma=1, nu=0.1), freq=FALSE,
xlab="x", las=1, main="")
curve(dCS2e(x, mu=0.1, sigma=1, nu=0.1), from=0, add=TRUE, col="red")
## The Hazard function
par(mfrow=c(1,1))
curve(hCS2e(x, mu=1, sigma=0.1, nu =0.1), from=0, to=1, ylim=c(0, 10),
col=2, ylab="Hazard function", las=1)
par(old_par) # restore previous graphical parameters