Least-Squares, Sentinels and Substractive Optimally Localized Average
Abstract
We present with unified notations three approaches to linear parameter estimation: least-squares, sentinels, and Substrative Optimally Localized Average (SOLA). It becomes then obvious that the two last approaches correspond to the very same mathematical problem. This brings a new interpretation to sentinels, new computational tools to SOLA, and makes clear their link to the classical least-squares approach.