例 : 设 X , Y X,Y X,Y 相互独立 , X ∼ P ( λ 1 ) X\sim P(\lambda_1) X∼P(λ1) , Y ∼ P ( λ 2 ) Y\sim P(\lambda_2) Y∼P(λ2) , 求证 Z = X + Y Z=X+Y Z=X+Y 服从参数为 λ 1 + λ 2 \lambda_1 + \lambda_2 λ1+λ2 的泊松分布
证明 :
由题意 , X X X 的分布律为 P { X = i } = λ 1 i i ! e − λ 1 , i = 0 , 1 , 2 , ⋯ P\{X=i\}=\frac{\lambda_1^i}{i!}e^{-\lambda_1},i=0,1,2,\cdots P{X=i}=i!λ1ie−λ1,i=0,1,2,⋯
Y Y Y 的分布律为 P { Y = i } = λ 2 i i ! e − λ 2 , i = 0 , 1 , 2 , ⋯ P\{Y=i\}=\frac{\lambda_2^i}{i!}e^{-\lambda_2},i=0,1,2,\cdots P{Y=i}=i!λ2ie−λ2,i=0,1,2,⋯
Z Z Z 的可能取值为 0 , 1 , 2 , ⋯ 0,1,2,\cdots 0,1,2,⋯ , Z Z Z 的分布律为 P { Z = k } = P { X + Y = k } = ∑ i = 0 k P { X = i } P { Y = k − i } = ∑ i = 0 k λ 1 i λ 2 k − i i ! ( k − i ) ! e − λ 1 e − λ 2 = e − ( λ 1 + λ 2 ) k ! ∑ i = 0 k k ! λ 1 i λ 2 k − i i ! ( k − i ) ! = e − ( λ 1 + λ 2 ) k ! ∑ i = 0 k C k i λ 1 i λ 2 k − i = ( λ 1 + λ 2 ) k k ! e − ( λ 1 + λ 2 ) P\{Z=k\}=P\{X+Y=k\}=\sum_{i=0}^{k}P\{X=i\}P\{Y=k-i\}=\sum_{i=0}^k\frac{\lambda_1^i \lambda_2^{k-i}}{i!(k-i)!}e^{-\lambda_1}e^{-\lambda_2}=\frac{e^{-(\lambda_1+\lambda_2)}}{k!}\sum_{i=0}^k\frac{k!\lambda_1^i \lambda_2^{k-i}}{i!(k-i)!}=\frac{e^{-(\lambda_1+\lambda_2)}}{k!}\sum_{i=0}^{k}C_k^i\lambda_1^i\lambda_2^{k-i}=\frac{(\lambda_1+\lambda_2)^k}{k!}e^{-(\lambda_1+\lambda_2)} P{Z=k}=P{X+Y=k}=∑i=0kP{X=i}P{Y=k−i}=∑i=0ki!(k−i)!λ1iλ2k−ie−λ1e−λ2=k!e−(λ1+λ2)∑i=0ki!(k−i)!k!λ1iλ2k−i=k!e−(λ1+λ2)∑i=0kCkiλ1iλ2k−i=k!(λ1+λ2)ke−(λ1+λ2)
k = 0 , 1 , 2 , ⋯ k=0,1,2,\cdots k=0,1,2,⋯
类似地,可以证明, X ∼ B ( n 1 , p ) , Y ∼ B ( n 2 , p ) X\sim B(n_1,p),Y\sim B(n_2,p) X∼B(n1,p),Y∼B(n2,p) , 则 Z = X + Y ∼ B ( n 1 + n 2 , p ) 则\,Z=X+Y \sim B(n_1+n_2,p) 则Z=X+Y∼B(n1+n2,p)