## Abstract

For evaluating the performance of color-difference equations, several goodness-of-fit measures were proposed in the past, such as Pearson’s correlation coefficient (*r*), the performance factor $PF/3$, and the recently proposed standardized residual sum of squares (*STRESS*) measure. The *STRESS* shares its main advantage, which is the possibility to statistically test performance differences, with the correlation coefficient. We show, by mathematical analysis supported by instructive numerical examples, that the *STRESS* has no meaningful interpretation in this regression analysis context. In addition, we present objections to the use of the *STRESS* for evaluating color- difference equations. Therefore, we recommend using the correlation coefficient in combination with a graphical and diagnostics analysis to ensure proper application as with any statistical technique.

© 2011 Optical Society of America

Full Article | PDF Article**OSA Recommended Articles**

Manuel Melgosa, Rafael Huertas, and Roy S. Berns

J. Opt. Soc. Am. A **25**(7) 1828-1834 (2008)

Manuel Melgosa, Pedro A. García, Luis Gómez-Robledo, Renzo Shamey, David Hinks, Guihua Cui, and M. Ronnier Luo

J. Opt. Soc. Am. A **28**(5) 949-953 (2011)

Pedro A. García, Rafael Huertas, Manuel Melgosa, and Guihua Cui

J. Opt. Soc. Am. A **24**(7) 1823-1829 (2007)