  In this paper, several modifications are introduced to the functional
approximation method iterLap to reduce the approximation error, including
stopping rule adjustment, proposal of new residual function, starting point
selection for numerical optimisation, scaling of Hessian matrix. Illustrative
examples are also provided to show the trade-off between running time and
accuracy of the original and modified methods.
