泊松分布描述的是给定的某段时间内，事件发生的概率
1.Poisson Process
1.1 Counting process
independent increment
注：增量是独立并且稳定的，同样服从泊松分布！！！！这个实际上是无记忆性！
Mean, Variance
下面通过例子理解：
如何构建泊松过程：
泊松过程描述的是给定的时间t之前发生的事件总数！！
1.2 Definition
关于泊松分布的定义，有以下两种
1.3 Properties
1.3.1 Decomposition
1.3.2 Superposition
举例应用：
1.4 Conditioanal distribution of arrival times
1.4.1
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In other words, the time of the event should be uniformly distributed over [0, t].
1.4.2 Order statistics
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Let Y1,Y2,...,Yn be n random variables. We say that Y(1),Y(2),...,Y(n) are the corresponding order statistics if Y(k) is the k th smallest
value among Y1,Y2,...,Yn.
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For instance,
(Y1,Y2,Y3)=(4,5,1)
The corresponding order statistics are(Y(1),Y(2),Y(3))=(1,4,5).
下面是例子：
