Response to 'Comments on construction of confidence intervals in connection with partial least squares'
Recently, Denham, Phatak and co-workers, and Faber and Kowalski have proposed local linearization to obtain prediction intervals when partial least squares has been used as estimation method. This approach has been criticized by Morsing and Ekman to ignore bias in the regression coefficient estimates (J. Chemometrics 1998; 12: 295-299), This response shows that, in contrast with Morsing and Ekman's claims, considerable attention has been paid to bias in the original work. In addition, it is explained that in typical chemometrics applications (inverse calibration of, for example, near-infrared spectroscopic data) bias is likely to be small, which implies that the original local linearization approach is potentially useful in practice. Finally, a method is proposed to include non-negligible bias in the regression coefficient estimates in the prediction intervals. Copyright (C) 2000 John Wiley gr Sons, Ltd.
partial least squares local linearization prediction interval bias