pub enum QuasiNewtonMethod {
    StationaryNewton,
    JacobianUpdate(UpdateQuasiNewtonMethod),
    InverseJacobianUpdate(UpdateQuasiNewtonMethod),
}
Expand description

Quasi-Newton methods are less computationnaly expensive than the Newton-Raphson method.

However, the most robust method is the Newton-Raphson one.

Quasi-newton methods do not evaluate the jacobian at each steps.

It is a trade off between recomputing the full jacobian matrix (which can take time, especially when using finite-differences) and the accuracy of the jacobian matrix used. Indeed, the more accurate the jacobian, fewer iterations will be needed.

Variants

StationaryNewton

The first computed jacobian will be used for all iterations.

JacobianUpdate(UpdateQuasiNewtonMethod)

The update of the methods will be performed on the jacobian matrix: it will be inverted afterwards before applying the step update.

InverseJacobianUpdate(UpdateQuasiNewtonMethod)

The update of the methods will be performed directly on the inverse jacobian matrix: Thus the jacobian won’t be computed at all after the first step.

Trait Implementations

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Auto Trait Implementations

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