Stochastic process
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In probability theory, a stochastic (Template:IPAc-en) process, or often random process, is a collection of random variables, representing the evolution of some system of random values over time. This is the probabilistic counterpart to a deterministic process (or deterministic system). Instead of describing a process which can only evolve in one way (as in the case, for example, of solutions of an ordinary differential equation), in a stochastic or random process there is some indeterminacy: even if the initial condition (or starting point) is known, there are several (often infinitely many) directions in which the process may evolve.
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See also
- List of stochastic processes topics
- Covariance function
- Dynamics of Markovian particles
- Entropy rate (for a stochastic process)
- Ergodic process
- Gillespie algorithm
- Interacting particle system
- Law (stochastic processes)
- Markov chain
- Probabilistic cellular automaton
- Random field
- Randomness
- Stationary process
- Statistical model
- Stochastic calculus
- Stochastic control
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