We investigate a novel adaptive choice rule of the Tikhonov regularization parameter in numerical differentiation which is a classic ill-posed problem. By assuming a ...

We demonstrate the flexibility and ease of use of C++ algorithmic differentiation (AD) tools based on overloading through application to numerical patterns (kernels) arising in computational finance.

The complex-step method is a clever way of obtaining a numerical approximation to the first derivative of a function, avoiding the round-off error that plagues ...