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cdfkap

Kappa distribution


Description

Distribution function and quantile function of the kappa distribution.

Usage

cdfkap(x, para = c(0, 1, 0, 0))
quakap(f, para = c(0, 1, 0, 0))

Arguments

x

Vector of quantiles.

f

Vector of probabilities.

para

Numeric vector containing the parameters of the distribution, in the order xi, alpha, k, h (location, scale, shape, shape).

Details

The kappa distribution with location parameter xi, scale parameter alpha and shape parameters k and h has quantile function

x(F) = xi + alpha (1 - ( (1-F^h)/h )^k) / k .

Its special cases include the generalized logistic (h=-1), generalized extreme-value (h=0), generalized Pareto (h=1), logistic (k=0, h=-1), Gumbel (k=0, h=0), exponential (k=0, h=1), and uniform (k=1, h=1) distributions.

Value

cdfkap gives the distribution function; quakap gives the quantile function.

Note

The functions expect the distribution parameters in a vector, rather than as separate arguments as in the standard R distribution functions pnorm, qnorm, etc.

References

Hosking, J. R. M. (1994). The four-parameter kappa distribution. IBM Journal of Research and Development, 38, 251-258.

Hosking, J. R. M., and Wallis, J. R. (1997). Regional frequency analysis: an approach based on L-moments, Cambridge University Press, Appendix A.10.

See Also

cdfglo for the generalized logistic distribution, cdfgev for the generalized extreme-value distribution, cdfgpa for the generalized Pareto distribution, cdfgum for the Gumbel distribution, cdfexp for the exponential distribution.

Examples

# Random sample from the kappa distribution
# with parameters xi=0, alpha=1, k=-0.5, h=0.25.
quakap(runif(100), c(0,1,-0.5,0.25))

lmom

L-Moments

v2.8
Common Public License Version 1.0
Authors
J. R. M. Hosking
Initial release
2019-03-11

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