In probability theory, a Poisson process is a stochastic process which counts the number of events and the time that these events occur in a given time interval. The time between each pair of consecutive events has an exponential distribution with parameter λ and each of these inter-arrival times is assumed to be independent of other inter-arrival times. The process is named after the French mathematician Siméon-Denis Poisson and is a good model of radioactive decay, telephone calls and requests for a particular document on a web server, among many other phenomena.
The Poisson process is a continuous-time process; the sum of a Bernoulli process can be thought of as its discrete-time counterpart. A Poisson process is a pure-birth process, the simplest example of a birth-death process. It is also a point process on the real half-line.
Read more about Poisson Process: Definition, Characterisation, Properties, Applications, Occurrence
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“Thinking is seeing.... Every human science is based on deduction, which is a slow process of seeing by which we work up from the effect to the cause; or, in a wider sense, all poetry like every work of art proceeds from a swift vision of things.”
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