It is usually expressed as an interval of parameter values at a certain confidence level, say, 95%.
In this context, it is typical to identify an interval of parameter values that imply equivalence of the two treatments (range of equivalence).
But in fact in most cases, they are pseudoinsensitive, mainly caused by too large a sampling interval of parameter values in sensitivity analysis calculations.
The small-amplitude oscillations in this map are stable, and the invariant circles exhibit a canard explosion over an interval of parameter values.
The 95% confidence interval is often misunderstood as the range of parameter values that includes the true value with 95% probability, a so-called credal interval: \[ P \theta \in [\hat{\theta} - \Delta, \hat{\theta} + \Delta]) = 0.95.
The worst-case scenario is the key aspect of the robust interval optimization model; it is a set of parameter values such that the security for any other scenarios can be guaranteed if and only if there is a feasible solution under this scenario [32, 33, 34, 35].
The uniform pdf is adopted in the following two main cases: (i) when it is known only a putative range for the parameter values; (ii) when it is useful to have a homogeneously spread set of parameter values within an interval of interest.
The size of suggested parameter changes was adjusted according to the observed sensitivity of the model to changes in the parameters at any given time and the total range of parameter values was hard-limited to specific intervals (see Methods).
aIn square brackets are the intervals of the parameter values, 'm' is the motif group and '~m' the non-motif group.
The uncertainties (length of the 95%% confidence interval) are large for a significant number of parameters values for all functions, independent of the functional alternative in the selected models.
