when we increase the original value of $k_1$ by 10 percent. Figures \[sens-fig01\]b, e and h show the same for the moments estimated using our proposed approach with 6 central moments (6m). Figures \[sens-fig01\]c, f and i show sensitivity coefficients estimated from both the SSA and 6m outputs using a finite difference approximation (in the 6m case, the sensitivity coefficients may instead be obtained automatically using the CVODES solver, which yields identical results). There is generally good agreement between the coefficients estimated using the two different approaches. However, as we consider higher moments, our ability to assess sensitivity using the SSA output rapidly diminishes, since the variability caused by the change in the parameter value is overwhelmed by the variability in the estimator due to finite sample size. This may be rectified by increasing the number of SSA simulations, but at considerable computational cost. In contrast, the sensitivity coefficients associated with higher moments may still be straightforwardly calculated using the moment expansion approach (although, of course, care must be taken to ensure that appropriately many moments have been taken into account by the approximation — see Section III E).

Simple Heuristics for Moment Expansions
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Our results for the p53 