Comparison of two recently proposed expressions for partial least squares regression prediction error

Two recently proposed expressions for partial least squares (PLS) predictio n error are compared. Using extensive Monte Carlo simulations, it is found. that the expression based on the so-called errors-in-variables approach yi elds prediction intervals with coverage probabilities close to their nomina l value, whereas the expression, which is implemented in the latest version of Unscrambler (7.0), is found to behave unsatisfactorily. The difference between the two approaches is illustrated on a real near-infrared data set taken from the literature. (C) 2000 Elsevier Science B.V. All rights reserv ed.