Some recent developments in PLS modeling
Some recent developments in PLS modeling
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DOI：
10.1016/s0169-7439(01)00156-3
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发表时间：
2001-10-28
影响因子：
3.9
通讯作者：
Antti, H
中科院分区：
文献类型：
--
作者：
Wold, S;Trygg, J;Antti, H
原始的化学计量学偏最小二乘（PLS）模型具有两个变量（X和Y），彼此线性相关，自1980年初以来已经进行了多次增强/扩展。在这里，我们讨论了多块和分层PLS建模安装的先验知识的数据结构和简化模型的解释，变量选择方案PLS往往类似的目标，非线性PLS，和预滤波PLS，正交信号校正（OSC）。最近的发展，正交化PLS（O-PLS）包括作为一种方式来完成OSC，和一个更简单的解释PLS模型。在这种情况下，我们还简要地提到时间序列，批处理，和小波的PLS.These PLS扩展说明肽的定量结构活性关系（QSAR）和纸浆的多变量表征使用近红外光谱的例子。(C)2001 Elsevier Science B. V.保留所有权利。
The original chemometrics partial least squares (PLS) model with two blocks of variables (X and Y), linearly related to each other, has had several enhancements/extensions since the beginning of 1980. We here discuss multi-block and hierarchical PLS modeling for installing a priori knowledge of the data structure and simplifying the model interpretation, variable selection schemes for PLS with often similar objectives, nonlinear PLS, and prefiltered PLS, orthogonal signal correction (OSC). A very recent development, orthogonalized-PLS (O-PLS) is included as a way to accomplish both OSC, and a simpler interpretation of the PLS model. In this context, we also briefly mention time series, batch, and wavelets variants of PLS.These PLS extensions are illustrated by examples from peptide quantitative structure-activity relationships (QSAR) and multivariate characterization of pulp using NIR. (C) 2001 Elsevier Science B.V. All rights reserved.