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2.5 多个随机变量的联合分布列

2.5 多个随机变量的联合分布列#

联合分布列的定义#

  • pX,Y(x,y)=P(X=x,Y=y)p_{X,Y}(x,y) = P(X = x, Y = y)
  • 描述两个随机变量同时取特定值的概率

边缘分布列#

  • pX(x)=ypX,Y(x,y)p_X(x) = \sum\limits_{y} p_{X,Y}(x,y)
  • pY(y)=xpX,Y(x,y)p_Y(y) = \sum\limits_{x} p_{X,Y}(x,y)
  • 计算方法:表格的行和与列和

随机变量函数的期望#

  • 一般函数E[g(X,Y)]=xyg(x,y)pX,Y(x,y)E[g(X,Y)] = \sum\limits_{x} \sum\limits_{y} g(x,y)p_{X,Y}(x,y)
  • 线性函数E[aX+bY+c]=aE[X]+bE[Y]+cE[aX + bY + c] = aE[X] + bE[Y] + c

多个随机变量的推广#

  • 三个随机变量pX,Y,Z(x,y,z)=P(X=x,Y=y,Z=z)p_{X,Y,Z}(x,y,z) = P(X = x, Y = y, Z = z)
  • 边缘分布pX,Y(x,y)=zpX,Y,Z(x,y,z)p_{X,Y}(x,y) = \sum\limits_{z} p_{X,Y,Z}(x,y,z)
  • 线性函数期望E[aX+bY+cZ+d]=aE[X]+bE[Y]+cE[Z]+dE[aX + bY + cZ + d] = aE[X] + bE[Y] + cE[Z] + d

一般线性组合#

对于X1,X2,,XnX_1, X_2, \cdots, X_n和常数a1,a2,,ana_1, a_2, \cdots, a_nE[i=1naiXi]=i=1naiE[Xi]E\left[\sum_{i=1}^n a_iX_i\right] = \sum_{i=1}^n a_iE[X_i]

2.5 多个随机变量的联合分布列
https://miku.nikonikoni.blog/posts/propability_theory/2-5-joint-probability-distribution/
Author
nikonikoni
Published at
2025-11-26
License
Unlicensed

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