![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=1739379548-TQvFP9ofzc0ifsNWsN2wxK9DglHyJo3k-0-c80999eef0fecb029a73ac948e34ebcd)
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=1739379548-nJ2FWo5jVBWTFhthKdR1ep9MlBrw3fXS-0-348397a9e3e6bd85701c50067a4d448b)
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=1739379548-ltYNLio2Ol33bX2oMHt9CxDO2aG8LOmS-0-a3bb8caa0fabf393c10cc9efacab8fee)
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=1739379548-u9qwpzR3qZlSyn1TADwU4OoBjDK8Xxyp-0-56ff45e41f4e82abf99296c7051700fd)
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=1739379548-auVlE9LISPt51BfUXkGCDLJLCtv8VvZL-0-9cfac2794b55d83b620f6660c2365d7b)
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_63.jpg?sign=1739379548-Bw3wHkdFbbwuw5khmAc4iYvANTttgiqD-0-b4d7e48cf29a6dbf3c96ad932d9a6e92)
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=1739379548-d0KaSE1lBG2loXSiAfNv0qwMW9RRodNh-0-f529213219b3b536068329969145b8ca)
如果X,Y,Z相互独立,则:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_65.jpg?sign=1739379548-BjdDFbxulURPcarbUtbMrfGIllXUlOjw-0-762440b9ab15b28c8541e7111d7e0690)
(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=1739379548-lAE5mQM5HznM8TNIzdWD1uV8v9DgSQeq-0-788527f6dab5c55638a0d482a1679358)
相应的条件重现期为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_67.jpg?sign=1739379548-fG58Q18KYewfuUbC3HJvdguhV5BOEFiD-0-d1af6b075a716941b09cb7946daca368)
如果X,Y,Z相互独立,则:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_68.jpg?sign=1739379548-MRngiCTJCV4Up8kUSnSu0MxBUqjrRafw-0-3303e5d0585dbea941cfd37e17dd85cd)
(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=1739379548-4GNHDKRv0n9VoYWQK7VICVRvTNZTmEO0-0-de30b3277c33aee916f8f8de36c93ffa)
相应的条件重现期为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_70.jpg?sign=1739379548-Qx6Nmw1ERMfFtPBzrEkP76gh9O0Fjuqk-0-3057a3a12bdd43079ddd0b5024b00182)
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=1739379548-m622ThGqyua0371JFzXqBek92AhcXiyY-0-c67c3e4f78e487192f1eed08d40c2bca)
相应的条件重现期为:
![img](https://epubservercos.yuewen.com/DF778D/19720710008529106/epubprivate/OEBPS/Images/txt003_72.jpg?sign=1739379548-RbwB54BP2otZn6HA4acpDaDlgKVWrHml-0-ba3909fa66f69fe31ca84d9460bf98f7)
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=1739379548-4jctuQ1pL2bAnvDYvTu56xAKfHypWYuH-0-4b2e0897b6427c1283fcba03ca6d51d9)
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=1739379548-VDk5dI98MK4QIP1NREPRxCY4X5f863Hb-0-3a45ffc8113092e020145dcfb63dfb51)
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。