Reconstruction of a strip geometry calorimeter using stepwise regression

An algorithm used to reconstruct events in a 2.44 m by 4.88 m three view electromagnetic calorimeter is presented. The least-squares fitting technique, stepwise regression, was adapted to this pattern recognition problem so that many possible combinations of particle candidates could be considered quickly. The result is an optimal set of particle candidates along with their positions and energy deposits.