mixinvgauss: Finite mixture of inverse Gaussian Distribution

In ACDm: Tools for Autoregressive Conditional Duration Models

Finite mixture of inverse Gaussian Distribution

Description

Density (PDF), distribution function (CDF), and hazard function for Finite mixture of inverse Gaussian Distributions.

Usage

dmixinvgauss(x, theta = .2, lambda = .1, gamma = .05, forceExpectation = F)
pmixinvgauss(q, theta = .2, lambda = .1, gamma = .05, forceExpectation = F)
mixinvgaussHazard(x, theta = .2, lambda = .1, gamma = .05, forceExpectation = F)

Arguments

x, q	vector of quantiles.
theta, lambda, gamma	parameters, see 'Details'.
forceExpectation	logical; if TRUE, the expectation of the distribution is forced to be 1..

Details

The finite mixture of inverse Gaussian distributions was used by Gomes-Deniz and Perez-Rodrigues (201X) for ACD-models. Its PDF is:

f(x) = \frac{γ + x}{γ + θ} √{\frac{λ}{2 π x^3}} \exp ≤ft[ - \frac{λ(x-θ)^2}{2 x θ^2}\right].

If forceExpectation = TRUE the distribution is transformed by dividing the random variable with its expectation and using the change of variable function.

References

Gomez-Deniz Perez-Rodriguez (201X) Non-exponential mixtures, non-monotonic financial hazard functions and the autoregressive conditional duration model. Working paper. Retrieved June 16, 2015, from http://dea.uib.es/digitalAssets/254/254084_perez.pdf.

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