### Abstract

Original language | English |
---|---|

Pages (from-to) | 239-245 |

Journal | Chemometrics and Intelligent Laboratory Systems |

Volume | 30 |

DOIs | |

Publication status | Published - 1995 |

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### Keywords

- PLS
- The Unscrambler

### Cite this

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**Prediction error in partial least squares (PLS) regression: a critique on the deviation used in The Unscrambler.** / de Vries, S.; ter Braak, C.J.F.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Prediction error in partial least squares (PLS) regression: a critique on the deviation used in The Unscrambler

AU - de Vries, S.

AU - ter Braak, C.J.F.

PY - 1995

Y1 - 1995

N2 - Partial least squares (PLS) regression is commonly used for multivariate calibration of instruments. Because of the need to know the quality of the prediction in a specific unknown sample and the lack of theory, an ‘empirically found formula’ to express the uncertainty is utilized in The Unscrambler II software, the de-facto standard in computer software for PLS. In this critique the formula is examined theoretically and by simulation. It is concluded that this formula underestimates the root mean squared error of prediction in most practical applications of PLS. A change of the formula is planned in the next version of The Unscrambler. In the mean time users of The Unscrambler ver 5.5 or lower should multiply the reported deviation by a factor of at least , to get a reasonable estimate of the prediction error

AB - Partial least squares (PLS) regression is commonly used for multivariate calibration of instruments. Because of the need to know the quality of the prediction in a specific unknown sample and the lack of theory, an ‘empirically found formula’ to express the uncertainty is utilized in The Unscrambler II software, the de-facto standard in computer software for PLS. In this critique the formula is examined theoretically and by simulation. It is concluded that this formula underestimates the root mean squared error of prediction in most practical applications of PLS. A change of the formula is planned in the next version of The Unscrambler. In the mean time users of The Unscrambler ver 5.5 or lower should multiply the reported deviation by a factor of at least , to get a reasonable estimate of the prediction error

KW - PLS

KW - The Unscrambler

KW - PLS

U2 - 10.1016/0169-7439(95)00030-5

DO - 10.1016/0169-7439(95)00030-5

M3 - Article

VL - 30

SP - 239

EP - 245

JO - Chemometrics and Intelligent Laboratory Systems

JF - Chemometrics and Intelligent Laboratory Systems

SN - 0169-7439

ER -