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#Com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde Classes and Interfaces - 15 results found.
| Name | Description | Type | Package | Framework |
| ConstantDriftVector | The class represents a constant drift function. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients | SuanShu |
| ConstantSigma1 | The class represents a constant diffusion coefficient function. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients | SuanShu |
| ConstantSigma2 | The class represents a constant diffusion coefficient function. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients | SuanShu |
| DiffusionMatrix | Interface | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients | SuanShu | |
| DiffusionSigma | This class implements the diffusion term in the form of a diffusion matrix. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients | SuanShu |
| DriftVector | Interface | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients | SuanShu | |
| FtAdaptedRealFunction | Interface | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde | SuanShu | |
| FtAdaptedVectorFunction | Interface | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde | SuanShu | |
| MultivariateBrownianSDE | A multivariate Brownian motion is a stochastic process with the following properties. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.discrete | SuanShu |
| MultivariateDiscreteSDE | This interface represents the discrete approximation of a multivariate SDE. | Interface | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.discrete | SuanShu |
| MultivariateEulerSDE | The Euler scheme is the first order approximation of an SDE. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.discrete | SuanShu |
| MultivariateFt | This represents the concept 'Filtration', the information available at time t. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde | SuanShu |
| MultivariateFtWt | This is a filtration implementation that includes the path-dependent information,See Also:MultivariateFt | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde | SuanShu |
| MultivariateSDE | This class represents a multi-dimensional, continuous-time Stochastic Differential Equation (SDE) of this form: dX_t = mu(t,X_t,Z_t,. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde | SuanShu |
| ZeroDriftVector | This class represents a 0 drift function. | Class | com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients | SuanShu |