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Random variate generation for the generalized inverse Gaussian distribution

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Abstract

We provide a uniformly efficient and simple random variate generator for the entire parameter range of the generalized inverse Gaussian distribution. A general algorithm is provided as well that works for all densities that are proportional to a log-concave function φ, even if the normalization constant is not known. It requires only black box access to φ and its derivative.

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Acknowledgement

I would like to thank both referees.

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Authors and Affiliations

  1. School of Computer Science, McGill University, 3480 University Street, Montreal, Canada, H3A 2K6

    Luc Devroye

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  1. Luc Devroye
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Correspondence to Luc Devroye.

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Research sponsored by NSERC Grant A3456.

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Devroye, L. Random variate generation for the generalized inverse Gaussian distribution. Stat Comput 24, 239–246 (2014). https://doi.org/10.1007/s11222-012-9367-z

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  • DOI: https://doi.org/10.1007/s11222-012-9367-z

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