=>x
i
=1(i=1,…,n),故
=P{X
1
=1,X
2
=1,…,X
n
=1}=P{X
1
=1}P{X
2
=1}…P(X
n
=1}=

N≥max{x
i
}(i=1,…,n). 故N的最大似然估计量为
max(X
1
,X
2
,…,X
n
}的分布律为
=P{max{X
1
,X
2
,…,X
n
}=k} =
=P{X
1
≤k}P{X
2
≤k}…P{X
n
≤k}- P(X
1
≤k-1}P(X
2
≤k-1}…P(X
n
≤k-1}
