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# Gauss Hypergeometric Distribution

The four shape parameters are \(\alpha>0\), \(\beta>0\), \(-\infty < \gamma < \infty\), and \(z > -1\). The support is \(x\in\left[0,1\right]\).

\[\text{Let }C=\frac{1}{B\left(\alpha,\beta\right)\,_{2}F_{1}\left(\gamma,\alpha;\alpha+\beta;-z\right)}\]
\begin{eqnarray*} f\left(x;\alpha,\beta,\gamma,z\right) & = & Cx^{\alpha-1}\frac{\left(1-x\right)^{\beta-1}}{\left(1+zx\right)^{\gamma}}\\ \mu_{n}^{\prime} & = & \frac{B\left(n+\alpha,\beta\right)}{B\left(\alpha,\beta\right)}\frac{\,_{2}F_{1}\left(\gamma,\alpha+n;\alpha+\beta+n;-z\right)}{\,_{2}F_{1}\left(\gamma,\alpha;\alpha+\beta;-z\right)}\end{eqnarray*}

Implementation: `scipy.stats.gausshyper`