Kumaraswamy exponential distribution {dprop} | R Documentation |
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 ( |
b |
The strictly positive shape parameter of the Kumaraswamy distribution ( |
lambda |
The strictly positive parameter of the exponential distribution ( |
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 imranshakoor84@yahoo.com.
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
Examples
d_kexp(0.2,1,1)