Difference between revisions of "Stochastic process"
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(New page: A '''stochastic process''' is a probabilistic model of a system that evolves non-deterministically<ref>c.f. {{cite book | author=Kulkarni, V. G. | title=Modeling and Analysis of Stochastic...) |
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| − | A '''stochastic process''' is a probabilistic model of a system that evolves non-deterministically<ref>c.f. {{cite book | author=Kulkarni, V. G. | title=Modeling and Analysis of Stochastic Systems| publisher=Chapman & Hall | year=1995 | editor= | | + | A '''stochastic process''' is a [[probability|probabilistic]] model of a system that evolves non-deterministically.<ref>c.f. {{cite book | author=Kulkarni, V. G. | title=Modeling and Analysis of Stochastic Systems| publisher=Chapman & Hall | year=1995 | editor= | isbn=0-412-04991-0}}</ref> Statisticians determine the system by approximating a [[probability distribution]], which assigns a level of certainty to particular evolutions. When the probability is high, evolution will likely occur; when it is low, so is the likelihood of evolution. Statisticians often model stochastic processes by using [[Markov chain]]s, [[Monte Carlo method|Monte Carlo analysis]], [[Poisson distribution]]s, [[kinematics]] and [[cellular automata]]. Stochastic processes are used in varied fields such as [[demography]], [[ekistics]], [[geology]], [[nuclear]] [[physics]], [[astrology]], and [[paleontology]]. |
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Latest revision as of 19:46, July 13, 2016
A stochastic process is a probabilistic model of a system that evolves non-deterministically.[1] Statisticians determine the system by approximating a probability distribution, which assigns a level of certainty to particular evolutions. When the probability is high, evolution will likely occur; when it is low, so is the likelihood of evolution. Statisticians often model stochastic processes by using Markov chains, Monte Carlo analysis, Poisson distributions, kinematics and cellular automata. Stochastic processes are used in varied fields such as demography, ekistics, geology, nuclear physics, astrology, and paleontology.
References
- ↑ c.f. Kulkarni, V. G. (1995). Modeling and Analysis of Stochastic Systems. Chapman & Hall. ISBN 0-412-04991-0.
