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  2. Stochastic - Wikipedia

    en.wikipedia.org/wiki/Stochastic

    The term stochastic process first appeared in English in a 1934 paper by Joseph L. Doob. [1] For the term and a specific mathematical definition, Doob cited another 1934 paper, where the term stochastischer Prozeß was used in German by Aleksandr Khinchin, [22] [23] though the German term had been used earlier in 1931 by Andrey Kolmogorov. [24]

  3. Stochastic process - Wikipedia

    en.wikipedia.org/wiki/Stochastic_process

    The definition of a stochastic process varies, [67] but a stochastic process is traditionally defined as a collection of random variables indexed by some set. [ 68 ] [ 69 ] The terms random process and stochastic process are considered synonyms and are used interchangeably, without the index set being precisely specified.

  4. Stochastic simulation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_simulation

    A stochastic simulation is a simulation of a system that has variables that can change stochastically (randomly) with individual probabilities. [ 1 ] Realizations of these random variables are generated and inserted into a model of the system.

  5. Stochastic computing - Wikipedia

    en.wikipedia.org/wiki/Stochastic_computing

    Stochastic computing performs this operation using probability instead of arithmetic. Specifically, suppose that there are two random, independent bit streams called stochastic number s (i.e. Bernoulli processes ), where the probability of a 1 in the first stream is p {\displaystyle p} , and the probability in the second stream is q ...

  6. Stochastic optimization - Wikipedia

    en.wikipedia.org/wiki/Stochastic_optimization

    Stochastic optimization (SO) are optimization methods that generate and use random variables. For stochastic optimization problems, the objective functions or constraints are random. Stochastic optimization also include methods with random iterates .

  7. Stochastic programming - Wikipedia

    en.wikipedia.org/wiki/Stochastic_programming

    Stochastic dynamic programming is a useful tool in understanding decision making under uncertainty. The accumulation of capital stock under uncertainty is one example; often it is used by resource economists to analyze bioeconomic problems [ 10 ] where the uncertainty enters in such as weather, etc.

  8. Continuous-time stochastic process - Wikipedia

    en.wikipedia.org/wiki/Continuous-time_stochastic...

    In probability theory and statistics, a continuous-time stochastic process, or a continuous-space-time stochastic process is a stochastic process for which the index variable takes a continuous set of values, as contrasted with a discrete-time process for which the index variable takes only distinct values.

  9. Stopped process - Wikipedia

    en.wikipedia.org/wiki/Stopped_process

    In mathematics, a stopped process is a stochastic process that is forced to assume the same value after a prescribed (possibly random) time. Definition [ edit ]