Search Java Classes and Packages
#Com.numericalmethod.suanshu.analysis.differentiation.multivariate Classes and Interfaces - 8 results found.
| Name | Description | Type | Package | Framework |
| BorderedHessian | A bordered Hessian matrix consists of the Hessian of a multivariate function f, and the gradient of a multivariate function g. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |
| Gradient | The gradient of a scalar field is a vector field which points in the direction of the greatest rate of increase of the scalar field, and of which the magnitude is the greatest rate of change. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |
| GradientFunction | The gradient function, g(x), evaluates the gradient of a real scalar function f at a point x. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |
| Hessian | The Hessian matrix is the square matrix of the second-order partial derivatives of a multivariate function. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |
| HessianFunction | The Hessian function, H(x), evaluates the Hessian of a real scalar function f at a point x. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |
| Jacobian | The Jacobian matrix is the matrix of all first-order partial derivatives of a vector-valued function. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |
| JacobianFunction | The Jacobian function, J(x), evaluates the Jacobian of a real vector-valued function f at a point x. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |
| MultivariateFiniteDifference | A partial derivative of a multivariate function is the derivative with respect to one of the variables with the others held constant. | Class | com.numericalmethod.suanshu.analysis.differentiation.multivariate | SuanShu |