dgenf: The generalized F distribution

In ACDm: Tools for Autoregressive Conditional Duration Models

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(ε)= \frac{γ ε^{κ γ -1}[η+(ε/λ)^{γ}]^{-η-κ}η^{η}}{λ^{κ γ}B(κ,η)},

where B(κ,η)=\frac{Γ(κ)Γ(η)}{Γ(κ+η)} is the beta function.

ACDm documentation built on Nov. 16, 2022, 5:09 p.m.