pdfgep: Probability Density Function of the Generalized Exponential...

In wasquith/lmomco: L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions

Probability Density Function of the Generalized Exponential Poisson Distribution

Description

This function computes the probability density of the Generalized Exponential Poisson distribution given parameters (\beta, \kappa, and h) computed by pargep. The probability density function is

f(x) = \frac{\kappa h \eta}{[1 - \exp(-h)]^\kappa}{1 - \exp[-h + h\exp(-\eta x)}\times\exp[-h - \eta x + h\exp(-\eta x)]\mbox{,}

where F(x) is the nonexceedance probability for quantile x > 0, \eta = 1/\beta, \beta > 0 is a scale parameter, \kappa > 0 is a shape parameter, and h > 0 is another shape parameter.

Usage

pdfgep(x, para)

Arguments

x	A real value vector.
para	The parameters from pargep or vec2par.

Value

Probability density (f) for x.

Author(s)

W.H. Asquith

References

Barreto-Souza, W., and Cribari-Neto, F., 2009, A generalization of the exponential-Poisson distribution: Statistics and Probability, 79, pp. 2493–2500.

See Also

pdfgep, quagep, lmomgep, pargep

Examples

pdfgep(0.5, vec2par(c(10,2.9,1.5), type="gep"))
## Not run: 
x <- seq(0,3, by=0.01); ylim <- c(0,1.5)
plot(NA,NA, xlim=range(x), ylim=ylim, xlab="x", ylab="f(x)")
mtext("Barreto-Souza and Cribari-Neto (2009, fig. 1)")
K <- c(0.1, 1, 5, 10)
for(i in 1:length(K)) {
   gep <- vec2par(c(2,K[i],1), type="gep"); lines(x, pdfgep(x, gep), lty=i)
}

## End(Not run)

wasquith/lmomco documentation built on April 20, 2024, 7:20 p.m.