![水灾害防治中的多变量概率问题](https://wfqqreader-1252317822.image.myqcloud.com/cover/642/37204642/b_37204642.jpg)
3.3 三变量联合概率分布
3.3.1 三维联合概率分布函数及重现期
设X,Y,Z为具有相关关系的随机变量,其联合分布函数定义为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_58.jpg?sign=1739346878-QPbzrNeYqLsRoTt8LVeXbFdIVXtLD0OU-0-74918dc49a4f1104febd5ec4d22bc2a8)
式中:x,y,z分别为变量X,Y,Z的取值;F(x,y,z)为三维联合不超过概率。
则至少有一个变量被超过的联合重现期为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_59.jpg?sign=1739346878-896dXLXJyrW2lXl8unAvvAXfW5uUgVEl-0-2d6770e1b793481fbddea4307c96fa87)
当变量X,Y,Z相互独立时,其联合概率分布为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_60.jpg?sign=1739346878-mhwB8RLXb4iFOl4PLjm9bhxrs9q1Jd2L-0-05ac45a98247b7c03d4904ab1ea5043c)
则各变量相互独立时的联合重现期表示为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_61.jpg?sign=1739346878-9sHIJhWSbuL4NU0sZWZdP5Ojpg2Xlo3z-0-05a3ba733fff9a4b21065ec691dd26b5)
3.3.2 三维条件分布函数及重现期
设X,Y,Z为具有相关关系的随机变量,其联合概率密度函数为f(x,y,z);fX(x),fY(y),fZ(z)分别为X,Y,Z的边际概率密度函数,则:
(1)在Z=z条件下,事件(X≤x和Y≤y)的联合概率分布函数及概率密度函数为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_62.jpg?sign=1739346878-IFRtPiZ5h4Xvk1xFzPogVA36T6W6PgAt-0-dd99083c70bcf913ca63e8ed23472252)
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_63.jpg?sign=1739346878-ttoJ2wZNihIBwxXhNVBKVDnIebhHyFG5-0-5ea9421dcbaab0b10c7612934821abca)
相应的条件重现期表示为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_64.jpg?sign=1739346878-r2tqgbYYM2b5uE0pWIMELNjseQVbWc5K-0-aeb095bd96662e13d7eec665c7f13ef7)
如果X,Y,Z相互独立,则:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_65.jpg?sign=1739346878-cuDsZDsvyI84pC9OaMhqr9WwhHveGCmM-0-ac02e001e1beda58fa471e618a6b6d71)
(2)在Y=y,Z=z条件下,事件X≤x的联合概率分布函数及概率密度函数为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_66.jpg?sign=1739346878-1t99tkGTiASO7M2nhKZP300lZyWxToym-0-894dc1ea5fc856cbb02f5f344afd85c0)
相应的条件重现期为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_67.jpg?sign=1739346878-CUUoRA7rOyyaCCPjHAy9WRXyItqRS3oT-0-a8d107545b2be2517c840ab553ce6753)
如果X,Y,Z相互独立,则:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_68.jpg?sign=1739346878-9yceyjXrjtjZRow6FAWN7c58mx9E0GRy-0-ad182d32a331d1214c49ebcceeac833b)
(3)在Z≤z条件下,事件(X≤x和Y≤y)的联合概率分布函数为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_69.jpg?sign=1739346878-3BXkjALnQCxWBDFash8rAdrffe92l4ZN-0-ae1f62103c8a8d049cbc1f158bc3b9a4)
相应的条件重现期为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_70.jpg?sign=1739346878-aYaV9t5ljv5UM6DSq1PFfqan8Kd6JiXA-0-2eead6d50c381bc22f2b2debac51d4fc)
如果X,Y,Z相互独立,则:F(x,y|Z≤z)=FX(x)FY(y)。
(4)在Y≤y,Z≤z条件下,事件X≤x的联合概率分布函数为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_71.jpg?sign=1739346878-Zf3fPZHcsD7tWZZObmtpyAHHPnRvjIMZ-0-51c46c27d52aa81edcedccf3f698cd46)
相应的条件重现期为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_72.jpg?sign=1739346878-rId9tOgxR5T0W99NGh6jx2xsdbFIVJ98-0-42a65896b9358a75b2842fffca54ee8a)
3.3.3 三维联合概率分布模型
当变量维数n≥3,多变量联合概率分布问题因其复杂性难以有明确的解析表达式,只有在各变量均属正态分布时,其联合分布函数才会有解析表达式。
设三维随机向量X=(X1,X2,X3)服从参量为(μ,∑)的三维正态分布,记作X~N(μ,∑),则其概率密度函数为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_73.jpg?sign=1739346878-dd38AXlZdWSXSwxA9mxKZWkcdXISHjeK-0-7763b45a8ad6bda6a18485ecfc58cf23)
式中:μ=EX为数学期望向量;∑=DX=(X-EX)(X-EX)T为方差矩阵,∑-1为∑的逆矩阵;(X-μ)T为(X-μ)的转置;det∑表示矩阵∑的行列式。
各参数表达式如下:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_74.jpg?sign=1739346878-wlMaum6qdn6pXXkAqCyIjU0DKwOpqCf0-0-92b590b226c0e1b52610c414c8ce5888)
三维正态分布模型由于计算较为复杂,且需要对变量边际分布进行正态化转换会影响分析的准确性,因此,在实际中较少应用。