Finite mixture of inverse Gaussian Distributions | R Documentation |
Density (PDF), distribution function (CDF), and hazard function for Finite mixture of inverse Gaussian Distributions.
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)
x , q |
vector of quantiles. |
theta , lambda , gamma |
parameters, see 'Details'. |
forceExpectation |
logical; if |
The finite mixture of inverse Gaussian distributions was used by Gomes-Deniz and Perez-Rodrigues (2013) for ACD-models. Its PDF is:
f(x) = \frac{\gamma + x}{\gamma + \theta} \sqrt{\frac{\lambda}{2 \pi x^3}} \exp \left[ - \frac{\lambda(x-\theta)^2}{2 x \theta^2}\right].
If forceExpectation = TRUE
the distribution is transformed by dividing the random variable with its expectation and using the change of variable function.
Gomez-Deniz, E. and Perez-Rodriguez, J.V. (2016) Mixture Inverse Gaussian for Unobserved Heterogeneity in the Autoregressive Conditional Duration Model. Communications in Statistics - Theory and Methods, http://dx.doi.org/10.1080/03610926.2016.1200094
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