Gaunt–Merkle conjectured bounds for the median of the variance-gamma distribution

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Let X∼VG(r,θ,σ,μ)X\sim\mathrm{VG}(r,\theta,\sigma,\mu) with r,θ,σ>0r,\theta,\sigma>0, and let Med(X)\mathrm{Med}(X) denote its median. The parameters rr, θ\theta, σ\sigma, and μ\mu are the shape, skewness, scale, and location parameters, respectively.

Gaunt–Merkle median bounds conjecture. For r>0r>0,

μ+(r−1)θ<Med(X)<μ+rθe−2/3r<μ+(r−23+29r)θ,\mu+(r-1)\theta<\mathrm{Med}(X)<\mu+r\theta \mathrm{e}^{-2/3r}<\mu+\left(r-\frac{2}{3}+\frac{2}{9r}\right)\theta,

and, for r≥2r\geq 2,

Med(X)≤μ+(r+2log⁡2−2)θ.\mathrm{Med}(X)\leq\mu+(r+2\log 2-2)\theta.

Exact median formulas are available for some parameter values, but no general closed-form formula is known. The conjectured bounds are supported by numerical results, while accurate general bounds for the median remain unresolved.

References

Primary source

Adrian Fischer, Robert E. Gaunt and Andrey Sarantsev, “The Variance-Gamma Distribution: A Review”, arXiv:2303.05615 (2023).

Additional references

2 papers in this index state this conjecture (2021–2023). The statement above is taken from the most recent of them; the others are arXiv:2106.02897.

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