This new technique allows for vastly improved efficiency in the computation of error estimates for Subset Simulation.
Contrary to this expectation, the present study shows for the first time that the computation of error signals leading to adaptation differs between saccade types.
This iterative procedure involves computation of error integrals of a number of reduced models which are obtained by deletion of different combinations of complexes.
One particularly important aspect that we have not discussed here is the computation of error estimates for certifying that the simulation output of the reduced model is within some tolerance of the corresponding simulation output of the original model.
We are currently investigating the computation of error bounds based on the algebraic property of the Laplacian matrices and we foresee that this knowledge might allow us to directly obtain the optimal set of complexes to be deleted.
However, for the computation of error integral as described in the paper, it is necessary that the original network is asymptotically stable around a steady state, since the computation makes use of the steady state concentrations of some species of the network.
The RKHSM does not require discretization of the variables, i.e., time and space, it is not affected by computation round of errors and one is not faced with necessity of large computer memory and time.
Clustering was accounted for during the computation of standard errors.
Finally, the computation of standard errors for labor supply elasticity highlights the areas where male and female elasticity are significantly different, strengthening the case that monopsony differences relate to earnings differences for these workers.
Additionally, we have introduced a simple Monte Carlo method for the numerical computation of the errors, which removes some of the approximations in the analysis, can be applied both with and without shadow fading, and presents a computational load much smaller than that of the direct simulation of the transmission.
