Figure 2

Determination of the linearity rejection region by Monte Carlo simulations. 3–150 samples were used from linear functions which were imposed by additional Gaussian noise. The example for m = 20 is shown, for which in some cases, fewer than 20 samples were returned due to outliers that were caused by the imposed technical error. For each of these m_return values, adapted maximum likelihood limits were determined for which the null hypothesis, the existence of a linearity, would need to be rejected.