Evaluating black boxes: an ad-hoc method for assessing nonparametric and nonlinear curve-fitting estimators

In many areas of science, novel curve-fitting algorithms are recommended and employed. Users often are left with little means of discerning whether or not the algorithms work as advertised. We propose an ad-hoc method for assessing the behavior of these estimators. By modifying a chemical technique called standard addition, we can assess 1) whether the estimator is responds sensibly to changes in the model and residual distribution and 2) possibly detect outliers or extreme points.