Higher Partials of fStress. Who Needs Them ?
We define fDistances, which generalize Euclidean distances, squared distances, and log distances. The least squares loss function to fit fDistances to dissimilarity data is fStress. We give formulas and R/C code to compute partial derivatives of orders one to four of fStress, relying heavily on the use of Faà di Bruno’s chain rule formula for higher derivatives.