BUILT-IN MATHEMATICA SYMBOL

ItoProcess

ItoProcess[{a, b}, x, t]
represents an Ito process , where .

ItoProcess[{a, b, c}, x, t]
represents an Ito process , where .

ItoProcess[..., {x, x0}, {t, t0}]
uses initial condition .

ItoProcess[..., ..., ..., ]
uses a Wiener process , with covariance .

ItoProcess[proc]
converts proc to a standard Ito process whenever possible.

ItoProcess[sdeqns, expr, x, t, wdproc]
represents an Ito process specified by a stochastic differential equation sdeqns, output expression expr, with state x and time t, driven by w following the process dproc.

Details and OptionsDetails and Options

• ItoProcess is also known as Ito diffusion.
• ItoProcess is a continuous-time and continuous-state random process.
• If the drift a is an -dimensional vector and the diffusion b an ×-dimensional matrix, the process is -dimensional and driven by an -dimensional WienerProcess.
• Common specifications for coefficients a and b include:
•  a scalar, b scalar a scalar, b vector a vector, b vector a vector, b matrix
• A stochastic differential equation is sometimes written as an integral equation .
• The default initial time is taken to be zero, and the default initial state is zero.
• The default covariance is the identity matrix.
• A standard Ito process has output , consisting of a subset of differential states .
• Processes proc that can be converted to standard ItoProcess form include OrnsteinUhlenbeckProcess, GeometricBrownianMotionProcess, StratonovichProcess, and ItoProcess.
• Converting an ItoProcess to standard form automatically makes use of Ito's lemma.
• The stochastic differential equations in sdeqns can be of the form , where is \[DifferentialD], which can be input using EscddEsc. The differentials and are taken to be Ito differentials.
• The output expression expr can be any expression involving and t.
• The driving process dproc can be any process that can be converted to a standard Ito process.
• Method settings in RandomFunction specific to ItoProcess include:
•  "EulerMaruyama" Euler-Maruyama (order 1/2, default) "KloedenPlatenSchurz" Kloeden-Platen-Schurz (order 3/2) "Milstein" Milstein (order 1) "StochasticRungeKutta" 3-stage Rossler SRK scheme (order 1) "StochasticRungeKuttaScalarNoise" 3-stage Rossler SRK scheme for scalar noise (order 3/2)
• ItoProcess can be used with such functions as RandomFunction, CovarianceFunction, PDF, and Expectation.

ExamplesExamplesopen allclose all

Basic Examples (1)Basic Examples (1)

Define a process by its stochastic differential equation:

 Out[1]=

Simulate the process:

 Out[2]=
 Out[3]=

Compute mean function:

 Out[4]=

Compute covariance function:

 Out[5]=
 Out[6]=