【徹底解説】多変量正規分布とは | Academaid\begin{align} f_{\mX}(\vx) &= \frac{1}{(2\pi)^{D/2}|\Sigma|^{1/2}}\exp \left\{ -\frac{1}{2}(\vx-\vmu)^T \Sigma^{-1}(\vx-\vmu) \right\} \\[0.7em] M_{\mX}(\vt) &= \exp\left( \vmu^T\vt + \frac{1}{2}\vt^T\Sigma\vt \right) \\[0.7em] E[\mX] &= \vmu \\[0.7em] V[\mX] &= \Sigma \end{align}
