kexp: Compute the distributional properties of the Kumaraswamy...

In dprop: Computation of Some Important Distributional Properties

Compute the distributional properties of the Kumaraswamy exponential distribution

Description

Compute the first four ordinary moments, central moments, mean, and variance, Pearson's coefficient of skewness and kurtosis, coefficient of variation, median and quartile deviation based on the selected parametric values of the Kumaraswamy exponential distribution.

Usage

d_kexp(lambda, a, b)

Arguments

a	The strictly positive shape parameter of the Kumaraswamy distribution (a > 0).
b	The strictly positive shape parameter of the Kumaraswamy distribution (b > 0).
lambda	The strictly positive parameter of the exponential distribution (\lambda > 0).

Details

The following is the probability density function of the Kumaraswamy exponential distribution:

f(x)=ab\lambda e^{-\lambda x}\left(1-e^{-\lambda x}\right)^{a-1}\left\{ 1-\left(1-e^{-\lambda x}\right)^{a}\right\} ^{b-1},

where x > 0, a > 0, b > 0 and \lambda > 0.

Value

d_kexp gives the first four ordinary moments, central moments, mean, and variance, Pearson's coefficient of skewness and kurtosis, coefficient of variation, median and quartile deviation based on the selected parametric values of the Kumaraswamy exponential distribution.

Author(s)

Muhammad Imran.

R implementation and documentation: Muhammad Imran [e-mail].

References

Cordeiro, G. M., & de Castro, M. (2011). A new family of generalized distributions. Journal of Statistical Computation and Simulation, 81(7), 883-898.

See Also

d_kburr, d_kum

Examples

d_kexp(0.2,1,1)

dprop documentation built on July 9, 2023, 6:40 p.m.