Multivariate Random Variable

deejayosamu·2025년 6월 23일

통계 기본 개념

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Discrete case

  • Joint pmf of X=(X1,...,Xn)\underline{X}=(X_1,...,X_n)

    PX(x)=PX1,...,Xn(x1,...,xn)=P(X1=x1,...,Xn=xn)P_{\underline{X}} (\underline{x}) = P_{X_1,...,X_n} (x_1,...,x_n) = P(X_1=x_1,...,X_n=x_n)

    properties)
    0PX(x)10 \leq P_{\underline{X}} (\underline{x}) \leq 1
    xsupportPX(x)=1\sum_{ \underline{x} \in support} P_{\underline{X}} (\underline{x})=1

  • Joint cdf of X\underline{X}

    FX(x)=FX1,...,Xn(x1,...,xn)=P(X1x1,...,Xnxn)F_{\underline{X}}(\underline{x}) = F_{X_1,...,X_n} (x_1,...,x_n) = P(X_1 \leq x_1,...,X_n \leq x_n)

  • Marginal pmf of XiX_i

    Let X=(x1,x2),\underline{X}=(x_1,x_2), then
    PX1(x1)=x2PX1,X2(x1,x2)P_{X_1} (x_1) = \sum_{x_2} P_{X_1,X_2} (x_1,x_2)
    PX2(x2)=x1PX1,X2(x1,x2)P_{X_2} (x_2) = \sum_{x_1} P_{X_1,X_2} (x_1,x_2)

  • Conditional pmf

    Let X=(x1,x2),\underline{X}=(x_1,x_2), then
    PX1X2(x1x2)=PX1,X2(x1,x2)PX2(x2)P_{X_1|X_2} (x_1|x_2) = \frac{P_{X_1,X_2} (x_1,x_2)}{P_{X_2} (x_2)}

Continuous case

  • Joint cdf of X\underline{X}

    FX1,...,Xn(x1,...,xn)=P(X1x1,...,Xnxn)=x1...xnfX1,...,Xn(t1,...,tn)dtn...dt1F_{X_1,...,X_n} (x_1,...,x_n) = P(X_1 \leq x_1,...,X_n \leq x_n)=\int_{-\infty}^{x_1} ... \int_{-\infty}^{x_n} f_{X_1,...,X_n} (t_1,...,t_n) dt_n...dt_1

    Properties) bivariate case
    F(x1,x2)F(x_1,x_2) is non-decreasing in both x1x_1 and x2x_2

    limx1F(x1,x2)=limx2F(x1,x2)=0\displaystyle \lim_{x_1 \to -\infty} F(x_1,x_2) = \displaystyle \lim_{x_2 \to -\infty} F(x_1,x_2) = 0

    pf) limx1F(x1,x2)=x2f(t1,t2)dt1dt2=0 b/c f(t1,t2)dt1=0\displaystyle \lim_{x_1 \to -\infty} F(x_1,x_2) = \int_{-\infty}^{x_2} \int_{-\infty}^{-\infty}f(t_1,t_2) dt_1dt_2 = 0 \space b/c \space \int_{-\infty}^{-\infty}f(t_1,t_2) dt_1 = 0

    limx1F(x1,x2)=FX2(x2),limx2F(x1,x2)=FX1(x1)\displaystyle \lim_{x_1 \to \infty} F(x_1,x_2) = F_{X_2} (x_2),\displaystyle \lim_{x_2 \to \infty} F(x_1,x_2) = F_{X_1} (x_1)

    pf) limx1F(x1,x2)=x2f(t1,t2)dt1dt2=x2f(t2)dt2=FX2(x2)\displaystyle \lim_{x_1 \to \infty} F(x_1,x_2) = \int_{-\infty}^{x_2} \int_{-\infty}^{\infty}f(t_1,t_2) dt_1dt_2 = \int_{-\infty}^{x_2} f(t_2)dt_2 = F_{X_2}(x_2)

    F(x1,x2)F(x_1,x_2) is right-continuous in both x1x_1 and x2x_2

  • Joint pdf of X\underline{X}

    If FF is differentiable, the joint pdf of X\underline{X} is
    nFX1,...,Xn(x1,...,xn)x1...xn=fX1,...,Xn(x1,...,xn)\frac{\partial^n F_{X_1,...,X_n} (x_1,...,x_n)}{\partial x_1...\partial x_n} = f_{X_1,...,X_n} (x_1,...,x_n)

  • Marginal pdf of XjX_j

    ...fX1,...,Xn(x1,...,xn)dx1...dxj1dxj+1...dxn\int_{-\infty}^{\infty} ... \int_{-\infty}^{\infty} f_{X_1,...,X_n} (x_1,...,x_n) dx_1...dx_{j-1}dx_{j+1}...dx_n

  • Conditional pdf

    Let X=(x1,x2),\underline{X}=(x_1,x_2), then
    fX1X2(x1x2)=fX1,X2(x1,x2)fX2(x2)f_{X_1|X_2} (x_1|x_2) = \frac{f_{X_1,X_2}(x_1,x_2)}{f_{X_2}(x_2)}

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