Memorylessness
Waiting time property of certain probability distributions / From Wikipedia, the free encyclopedia
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In probability and statistics, memorylessness is a property of certain probability distributions. It describes situations where the time you've already waited for an event doesn't affect how much longer you'll have to wait. To model memoryless situations accurately, we have to disregard the past state of the system – the probabilities remain unaffected by the history of the process.[1]
Only two kinds of distributions are memoryless: geometric distributions of non-negative integers and the exponential distributions of non-negative real numbers.
In the context of Markov processes, memorylessness refers to the Markov property,[2] an even stronger assumption which implies that the properties of random variables related to the future depend only on relevant information about the current time, not on information from further in the past. The present article describes the use outside the Markov property.