标准正态分布k阶原点矩公式
今天在看χ2\chi^2χ2分布,计算其方差时,遇到了标准正态分布的四阶原点矩。书上直接写E(Xi4)=3E(X_i^4)=3E(Xi4)=3,很好奇。设Xi∼N(0,1)X_i\sim\mathcal{N}(0,1)Xi∼N(0,1)想根据定义计算:
E(Xi4)=∫−∞+∞x412πe−x22dxE(X_i^4)=\int_{-\infty}^{+\infty}x^4\frac{1}{\sqrt{2\pi}}e^{-\frac{x^2}{2}}dxE(Xi4)=∫−∞+∞x42π1e−2x2dx
计算起来复杂度有点高,K阶就更不敢想。
想着估计结果是kkk的递推关系式。所有直接计算:
E(Xk)=∫−∞+∞xk12πe−x22dx=1k+1xk+112πe−x22∣−∞+∞+1k+1∫−∞+∞xk+212πe−x22dx=0+1k+1E(Xk+2)
\begin{aligned}
E(X^k) &= \int_{-\infty}^{+\infty}x^k\frac{1}{\sqrt{2\pi}}e^{-\frac{x^2}{2}}dx \\
& = \frac{1}{k+1}x^{k+1}\frac{1}{\sqrt{2\pi}}e^{-\frac{x^2}{2}} |_{-\infty}^{+\infty} + \frac{1}{k+1}\int_{-\infty}^{+\infty}x^{k+2}\frac{1}{\sqrt{2\pi}}e^{-\frac{x^2}{2}}dx \\
& = 0 + \frac{1}{k+1}E(X^{k+2})
\end{aligned}
E(Xk)=∫−∞+∞xk2π1e−2x2dx=k+11xk+12π1e−2x2∣−∞+∞+k+11∫−∞+∞xk+22π1e−2x2dx=0+k+11E(Xk+2)
从上式看,结果已经很明显了,其递推关系为:
E(Xk)=(k−1)E(Xk−2),k=2,3,4⋯E(X^k) = (k-1)E(X^{k-2}),k=2,3,4\cdotsE(Xk)=(k−1)E(Xk−2),k=2,3,4⋯
其中:
E(X0)=∫−∞+∞x012πe−x22dx=1E(X^0)=\int_{-\infty}^{+\infty}x^0\frac{1}{\sqrt{2\pi}}e^{-\frac{x^2}{2}}dx=1E(X0)=∫−∞+∞x02π1e−2x2dx=1
E(X1)=0E(X^1)=0E(X1)=0
所以,当k=2ik=2ik=2i为偶数时:
E(Xk)=(k−1)(k−3)⋯3×1×E(X0)=∏i=1k/2(2i−1)
\begin{aligned}
E(X^k) &= (k-1)(k-3)\cdots3\times1\times E(X^0) \\
&=\prod_{i=1}^{k/2}(2i-1)
\end{aligned}
E(Xk)=(k−1)(k−3)⋯3×1×E(X0)=i=1∏k/2(2i−1)
当k=2i−1k=2i-1k=2i−1为奇数时:
E(Xk)=(k−1)(k−3)⋯3×1×E(X1)=0
\begin{aligned}
E(X^k) &= (k-1)(k-3)\cdots3\times1\times E(X^1) \\
&=0
\end{aligned}
E(Xk)=(k−1)(k−3)⋯3×1×E(X1)=0
综上有:
E(Xk)={∏i=1k/2(2i−1)k=2i,i=1,2,3⋯0k=2i−1
E(X^k) = \left \{
\begin{array}{ll}
\prod_{i=1}^{k/2}(2i-1) & k=2i, i=1,2,3\cdots \\
& \\
0 & k=2i-1
\end{array} \right.
E(Xk)=⎩⎨⎧∏i=1k/2(2i−1)0k=2i,i=1,2,3⋯k=2i−1