Geometrically transformed weights for least squares analyses

The most generalized algorithm for the least-squares estimation of parameters in nonlinear, implicit models is the modified Deming approach. This technique is very complicated; however, simpler approaches for many problems lead to reasonable solutions. One widely accepted alternative is the Δ transformation of Hust and McCarty. This article offers another equally simple alternative: geometrically transformed weights.