RelDists (version 1.0.0)

dQXGP: The Quasi XGamma Poisson distribution

Description

Density, distribution function,quantile function, random generation and hazard function for the Quasi XGamma Poisson distribution with parameters mu, sigma and nu.

Usage

dQXGP(x, mu, sigma, nu, log = FALSE)
pQXGP(q, mu, sigma, nu, lower.tail = TRUE, log.p = FALSE)
qQXGP(p, mu, sigma, nu, lower.tail = TRUE, log.p = FALSE)
rQXGP(n, mu, sigma, nu)
hQXGP(x, mu, sigma, nu)

Value

dQXGP gives the density, pQXGP gives the distribution function, qQXGP gives the quantile function, rQXGP

generates random deviates and hQXGP gives the hazard function.

Arguments

x, q

vector of quantiles.

mu

parameter.

sigma

parameter.

nu

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.

Author

Simon Zapata

Details

The Quasi XGamma Poisson distribution with parameters mu, sigma and nu has density given by:

\(f(x)= K(\mu, \sigma, \nu)(\frac {\sigma^{2} x^{2}}{2} + \mu) exp(\frac{\nu exp(-\sigma x)(1 + \mu + \sigma x + \frac {\sigma^{2}x^{2}}{2})}{1+\mu} - \sigma x),\)

for \(x > 0\), \(\mu> 0\), \(\sigma> 0\), \(\nu> 1\).

where

\(K(\mu, \sigma, \nu) = \frac{\nu \sigma}{(exp(\nu)-1)(1+\mu)}\)

References

subhradev2018RelDists

Examples

old_par <- par(mfrow = c(1, 1)) # save previous graphical parameters

## The probability density function
curve(dQXGP(x, mu=0.5, sigma=1, nu=1), from=0.1, to=8,
      ylim=c(0, 0.6), col="red", las=1, ylab="f(x)")

## The cumulative distribution and the Reliability function
par(mfrow=c(1, 2))
curve(pQXGP(x, mu=0.5, sigma=1, nu=1),
      from=0.1, to=8,  col="red", las=1, ylab="F(x)")
curve(pQXGP(x,  mu=0.5, sigma=1, nu=1, lower.tail=FALSE),
      from=0.1, to=8, col="red", las=1, ylab="R(x)")

## The quantile function
p <- seq(from=0, to=0.99999, length.out=100)
plot(x=qQXGP(p, mu=0.5, sigma=1, nu=1), y=p, xlab="Quantile",
     las=1, ylab="Probability")
curve(pQXGP(x, mu=0.5, sigma=1, nu=1),
      from=0.1, add=TRUE, col="red")
      
## The random function
hist(rQXGP(n=1000, mu=0.5, sigma=1, nu=1), freq=FALSE,
     xlab="x", ylim=c(0, 0.4), las=1, main="", xlim=c(0, 15))
curve(dQXGP(x, mu=0.5, sigma=1, nu=1),
      from=0.001, to=500, add=TRUE, col="red")

## The Hazard function
curve(hQXGP(x, mu=0.5, sigma=1, nu=1), from=0.01, to=3,
      col="red", ylab="Hazard function", las=1)

par(old_par) # restore previous graphical parameters