SciPy

This is documentation for an old release of SciPy (version 1.4.0). Read this page in the documentation of the latest stable release (version 1.15.1).

Chi Distribution

Generated by taking the (positive) square-root of chi-squared variates. The one shape parameter is \(\nu\), a positive integer, the degrees of freedom. The support is \(x\geq0\).

\begin{eqnarray*} f\left(x;\nu\right) & = & \frac{x^{\nu-1}e^{-x^{2}/2}}{2^{\nu/2-1}\Gamma\left(\frac{\nu}{2}\right)}\\ F\left(x;\nu\right) & = & \frac{\gamma\left(\frac{\nu}{2},\frac{x^{2}}{2}\right)}{\Gamma(\frac{\nu}{2})}\\ G\left(q;\nu\right) & = & \sqrt{2\gamma^{-1}\left(\frac{\nu}{2},q\Gamma(\frac{\nu}{2})\right)}\\ M\left(t\right) & = & \Gamma\left(\frac{v}{2}\right)\,_{1}F_{1}\left(\frac{v}{2};\frac{1}{2};\frac{t^{2}}{2}\right)+\frac{t}{\sqrt{2}}\Gamma\left(\frac{1+\nu}{2}\right)\,_{1}F_{1}\left(\frac{1+\nu}{2};\frac{3}{2};\frac{t^{2}}{2}\right)\\ \mu & = & \frac{\sqrt{2}\Gamma\left(\frac{\nu+1}{2}\right)}{\Gamma\left(\frac{\nu}{2}\right)}\\ \mu_{2} & = & \nu-\mu^{2}\\ \gamma_{1} & = & \frac{2\mu^{3}+\mu\left(1-2\nu\right)}{\mu_{2}^{3/2}}\\ \gamma_{2} & = & \frac{2\nu\left(1-\nu\right)-6\mu^{4}+4\mu^{2}\left(2\nu-1\right)}{\mu_{2}^{2}}\\ m_{d} & = & \sqrt{\nu-1}\quad\nu\geq1\\ m_{n} & = & \sqrt{2\gamma^{-1}\left(\frac{\nu}{2},\frac{1}{2}{\Gamma(\frac{\nu}{2})}\right)}\end{eqnarray*}

Implementation: scipy.stats.chi

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