Properties of the generalized inverse Gaussian with applications to Monte Carlo simulation and distribution function evaluation

Víctor Peña and Michael Jauch

Statistics & Probability Letters, 2025, vol. 220, issue C

Abstract: We introduce two mixture representations for the generalized inverse Gaussian (GIG) distribution. One mixture representation expresses the GIG as a continuous mixture of inverse Gaussians. The other reveals a relationship between GIGs. These mixture representations lead to new sampling methods and an exact algorithm for evaluating the distribution function of the GIG for half-integer p.

Keywords: Gibbs sampling; Markov chain Monte Carlo; Probability distributions; Random number generation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.spl.2025.110359

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