Guaranteed linear and nonlinear parameter estimation from bounded-error data: A survey

Classical statistical estimation has some drawbacks that can be overcome by bounded-error estimation, a deterministic alternative. Methods are presented that make it possible to obtain a set guaranteed to contain all parameter vectors consistent with the data, model structure and assumed error bounds. The techniques to be used depend on whether or not the error is affine in the parameters.<>