represents a Wiener process with a drift μ and volatility σ.
represents a standard Wiener process with drift 0 and volatility 1.
- WienerProcess is also known as Brownian motion, a continuous-time random walk, or integrated white Gaussian noise.
- WienerProcess is a continuous-time and continuous-state random process.
- The state at time t follows NormalDistribution[μ t,σ].
- The parameter μ can be any real number and the parameter σ can be any positive real number.
- WienerProcess can be used with such functions as Mean, PDF, Probability, and RandomFunction.
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Basic Examples (3)
Generalizations & Extensions (1)
Properties & Relations (11)
Neat Examples (3)
Introduced in 2012