11.5.2.1. Defining the percentile

The first method discussed here is straightforward: the principle of rejection is to keep the best-tested configurations. This can be done either by applying a threshold value on the distance results (called \(\delta\) in [Bla17]) or by retaining a fixed fraction of the tested configurations, defined through a percentile \(\varepsilon_{Dist}\). The TRejectionABC method implements the latter approach. By default, the percentile is set to \(\varepsilon_{Dist} = 0.01\).

To modify this value, the user can call setPercentile, whose prototype is

setPercentile(eps)

where the argument eps specifies the fraction of configurations to be kept.

An important consequence is that the total number of configurations evaluated is computed as follows:

\[n_{\rm Comp} = \frac{n_{S}}{\varepsilon_{Dist}}\]

where \(n_{S}\) is the number of retained samples in the final posterior distribution, as defined in the constructor (see Constructing the TRejectionABC object).