# Problems Estimating Parameters for the Inverse Gamma Distribution

I am trying to estimate the parameters of an inverse gamma distribution such that a given amount of probability mass lies above and below some specified threshold.

If $x$ is an inverse gamma distributed random variable $x \sim \mathrm{Inverse Gamma}(\alpha, \beta)$, I want to find $\alpha$ and $\beta$ such that:

$\displaystyle\int_{0}^{a} dx = r$

and

$\displaystyle\int_{b}^{\infty} dx = r$

I have attempted to solve the system of equations:

\begin{aligned} \Phi_{IG}(a| \alpha, \beta) - r = 0 \\ (1 - \Phi_{IG}(b| \alpha, \beta)) - r = 0 \end{aligned}

With $\Phi_{IG}$ being the Inverse Gamma CDF, but the solution obtained using scipy's nonlinear root finding module appears extremely sensitive to the initial guess and I am not aware of a principled means of determining it.

My Question:

Is there a principled method of determining initial values of $\alpha$ and $\beta$ to solve the problem in such a way? Are there more effective ways of identifying $\alpha$ and $\beta$ other than solving such a system of equations?

It appears my problem primarily occurs when initial values of $\alpha$ and $\beta$ fail to allocate any mass below/above $a$ and $b$, respectively, in which case the objective function described by the above system of equations is effectively flat on initialisation and no progress can be made.