Random values generation from the GEP, EP and PE distributions {geppe}

Random values generation from the GEP, EP and PE distributions

Description

Random values generation from the GEP, EP and PE distributions.

Usage

repois(n, beta, lambda)
rgep(n, beta, alpha, lambda)
rpe(n, theta, lambda)

Arguments

n

The sample size.

beta

A strictly positive number, the scale parameter (\beta).

alpha

A stritly positive number, the \alpha parameter of the GEP distribution. If a=1, then one ends up with the EP distribution.

theta

A strictly positive number, the shape parameter (\theta).

lambda

A strictly positive number, the shape parameter (\lambda).

Details

In order to generate values from these distributions the inverse rejection sampling is used.

Value

A vector with generated values from the GEP, EP or the PE distribution.

Author(s)

Sofia Piperaki.

R implementation and documentation: Sofia Piperaki [e-mail] and Michail Tsagris [e-mail].

References

Barreto-Souza W. and Cribari-Neto F. (2009). A generalization of the exponential-Poisson distribution. Statistics and Probability Letters, 79(24): 2493–2500.

Louzada F., Ramos P. L. and Ferreira H. P. (2020). Exponential-Poisson distribution: estimation and applications to rainfall and aircraft data with zero occurrence. Communications in Statistics-Simulation and Computation, 49(4): 1024–1043.

Rodrigues G. C., Louzada F. and Ramos P. L. (2018). Poisson-exponential distribution: different methods of estimation. Journal of Applied Statistics, 45(1): 128–144.

See Also

dgep

Examples

x <- rgep(100, 1, 2, 3)