GeneralizedGammaDist {ACDm} | R Documentation |
The generelized Gamma distribution
Description
Density (PDF), distribution function (CDF), quantile function (inverted CDF), random generation and hazard function for the generelized Gamma distribution with parameters gamma, kappa and lambda.
Usage
dgengamma(x, gamma = 0.3, kappa = 1.2, lambda = 0.3, forceExpectation = F)
pgengamma(x, gamma = .3, kappa = 3, lambda = .3, forceExpectation = F)
qgengamma(p, gamma = .3, kappa = 3, lambda = .3, forceExpectation = F)
rgengamma(n = 1, gamma = .3, kappa = 3, lambda = .3, forceExpectation = F)
gengammaHazard(x, gamma = .3, kappa = 3, lambda = .3, forceExpectation = F)
Arguments
x |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations.. |
gamma , kappa , lambda |
parameters, see 'Details'. |
forceExpectation |
logical; if |
Details
The PDF for the generelized Gamma distribution is:
f(x)=\frac{\gamma x^{\kappa \gamma - 1}}{\lambda^{\kappa \gamma}\Gamma (\kappa)}\exp \left\{{-\left(\frac{x}{\lambda}\right)^{\gamma}}\right\}
Value
dgengamma
gives the density (PDF), pgengamma
gives the distribution function (CDF), qgengamma
gives the quantile function (inverted CDF), rgenGamma
generates random deviates, and genGammaHazard
gives the hazard function.
Author(s)
Markus Belfrage