截断正态分布

正态分布被限制在由两个参数给出的一定范围内的正态分布 \(A\)\(B\) 。请注意,这是 \(A\)\(B\) 对应于 \(x\) 在标准形式下。为 \(x\in\left[A,B\right]\) 我们会得到

\Begin{eqnarray*}f\Left(x;A,B\Right)&=&\frac{\phi\left(x\right)}{\Phi\left(B\right)-\Phi\left(A\right)}\\ F\Left(x;A,B\Right)&=&\frac{\Phi\left(x\right)-\Phi\left(A\right)}{\Phi\left(B\right)-\Phi\left(A\right)}\\ G\Left(Q;A,B\Right)&=&\Phi^{-1}\left(q\Phi\left(B\right)+\Phi\left(A\right)\left(1-q\right)\right)\end{eqnarray*}

哪里

\BEGIN{eqnarray*}\phi\Left(x\right)&=&\frac{1}{\sqrt{2\pi}}e^{-x^{2}/2}\\ \Phi\Left(x\Right)&=&\int_{-\infty}^{x}\phi\left(u\right)du.\end{eqnarray*}
\BEGIN{等式*}\MU&=&\frac{\phi\left(A\right)-\phi\left(B\right)}{\Phi\left(B\right)-\Phi\left(A\right)}\\ \MU_{2}&=&1+\frac{A\phi\left(A\right)-B\phi\left(B\right)}{\Phi\left(B\right)-\Phi\left(A\right)}-\left(\frac{\phi\left(A\right)-\phi\left(B\right)}{\Phi\left(B\right)-\Phi\left(A\right)}\right)^{2}\end{eqnarray*}

实施: scipy.stats.truncnorm