Modeling of Inverse Gaussian Frailty Model for Bivariate Survival Data

Hanagal, David D.; Dabade, Alok D.

doi:10.1080/03610926.2011.638428

Cited by 12 publications

(1 citation statement)

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“…3 When modelling the unobserved heterogeneity of individuals, the inverse Gaussian distribution is also employed in frailty duration models (Hougard 1984, Hanagal & Dabade 2013. However, the reciprocal of the inverse Gaussian distribution (which is not commonly used by statisticians and has been little explored in the literature) allows us to introduce more flexibility and tractability into the modelling of scale parameters and to obtain closed form expressions for the infinite mixture.…”

Section: Introductionmentioning

confidence: 99%

Conditional Duration Model and Unobserved Market Heterogeneity of Traders. An Infinite Mixture of Non–Exponentials

Gómez–Déniz

Pérez‐Rodríguez

2016

Rev. colomb. estad.

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<p>This paper extends the conditional duration model proposed by De Luca and Zuccolotto (2003), proposing an infinite mixture of distributions based on non–exponentials which accounts for the unobserved market heterogeneity of traders. The model we propose takes into account the fact that reaction times follow a gamma distribution and that the intensity parameter follows the reciprocal of an inverse Gaussian distribution. This extension allows us to capture not only various density shapes of durations, but also non–monotonic shapes of hazard functions. The model also allows us to test the unobserved heterogeneity of traders. This mixture model is easy to fit and characterises the behaviour of the conditional durations reasonably well.</p>

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Section: Introductionmentioning

confidence: 99%