# dgenf: The generalized F distribution In ACDm: Tools for Autoregressive Conditional Duration Models

 dgenf R Documentation

## The generalized F distribution

### Description

Density and distribution function for the generalized F distribution. Warning: the distribution function pgenf and genfHazard are computed numerically, and may not be precise!

### Usage

dgenf(x, kappa = 5, eta = 1.5, gamma = .8, lambda = 1, forceExpectation = F)
pgenf(q, kappa = 5, eta = 1.5, gamma = .8, lambda = 1, forceExpectation = F)
genfHazard(x, kappa = 5, eta = 1.5, gamma = .8, lambda = 1, forceExpectation = F)


### Arguments

 x, q vector of quantiles. kappa, eta, gamma, lambda parameters, see 'Details'. forceExpectation logical; if TRUE, the expectation of the distribution is forced to be 1 by letting theta be a function of the other parameters.

### Details

The PDF for the generelized F distribution is:

f(\epsilon)= \frac{\gamma \epsilon^{\kappa \gamma -1}[\eta+(\epsilon/\lambda)^{\gamma}]^{-\eta-\kappa}\eta^{\eta}}{\lambda^{\kappa \gamma}B(\kappa,\eta)},

where B(\kappa,\eta)=\frac{\Gamma(\kappa)\Gamma(\eta)}{\Gamma(\kappa+\eta)} is the beta function.

ACDm documentation built on May 29, 2024, 12:04 p.m.