[SciPy-User] Mean, variance, and parametrisation of an inverse Gaussian distribution

[servant mathieu]

Dear scipy users,

The time for a diffusion process to reach a single evidence threshold a is
often modeled as an inverse Gaussian distribution with mean (a/σ) and
variance (a*σ2/μ3 ), where  μ represents the mean drift rate and  σ2  the
variance of the accumlulation process. How could I reparametrise the
scipy.stats.invgauss* * function to manipulate those parameters?

Cheers,
Mathieu
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