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major reference
- In statistics: Time series and forecasting
  A time series is a set of data collected at successive points in time or over successive periods of time. A sequence of monthly data on new housing starts and a sequence of weekly data on product sales are examples of…
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automata theory
- In automata theory: The automaton and its environment
  …data read from physically generated time series (or numerical values indexed consecutively in time and related through a transformation) could be extrapolated. He saw that, if this process could be accomplished with sufficient speed, as would be possible with modern electronic circuits, then the extrapolated values would be obtained faster…
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stochastic processes
- In stochastic process
  …(such as radioactive decay), and time series, with the index variable referring to time. This indexing can be either discrete or continuous, the interest being in the nature of changes of the variables with respect to time.
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work of

Engle
- In Robert F. Engle
  …development of methods for analyzing time series data with time-varying volatility. He shared the award with Clive W.J. Granger.
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Granger
- In Clive W.J. Granger
  …development of techniques for analyzing time series data with common trends. He shared the award with the American economist Robert F. Engle.
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stochastic process

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stochastic process

mathematics

Written and fact-checked by The Editors of Encyclopaedia Britannica

Last Updated: Jun 2, 2025 • Article History

Key People:: Norbert Wiener; Andrey Andreyevich Markov

Related Topics:: Markov chain; random walk; diffusion process; Ito stochastic calculus; reflecting barrier

See all related content

stochastic process, in probability theory, a process involving the operation of chance. For example, in radioactive decay every atom is subject to a fixed probability of breaking down in any given time interval. More generally, a stochastic process refers to a family of random variables indexed against some other variable or set of variables. It is one of the most general objects of study in probability. Some basic types of stochastic processes include Markov processes, Poisson processes (such as radioactive decay), and time series, with the index variable referring to time. This indexing can be either discrete or continuous, the interest being in the nature of changes of the variables with respect to time.