AoV-PLS: a new method for the analysis of multivariate data depending on several factors

被引：19

作者：

Angelina, El Ghaziri ^{[1
,2
]}

Qannari, El Mostafa ^{[1
,2
]}

Moyon, Thomas ^{[3
]}

Alexandre-Gouabau, Marie-Cecile ^{[3
]}

机构：

[1] LUNAM Univ, ONIRIS, Unite Sensometrie & Chimiometrie, F-44322 Nantes, France

[2] INRA, F-44307 Nantes, France

[3] INRA, UMR1280, Physiol Adaptat Nutr, F-44307 Nantes, France

来源：

ELECTRONIC JOURNAL OF APPLIED STATISTICAL ANALYSIS | 2015年 / 8卷 / 02期

关键词：

ANOVA; ANOVA-Simultaneous Component Analysis; ANOVA-PCA; PLS regression; PLS-DA; Metabolomics data;

D O I：

10.1285/i20705948v8n2p214

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A new method for the analysis of a multivariate dataset depending on several factors is proposed. It is called AoV-PLS (Analysis of VariancePLS). It is based on the decomposition of the dataset into the main effects, the interactions effects and possibly the residual matrix using a model akin to analysis of variance (ANOVA). Each effect is considered in turn and assessed through the use of a Partial Least Square regression (PLS-regression). The connection of AoV-PLS to competing methods such as ANOVA-PCA and ANOVA-Simultaneous Component Analysis (ASCA) is emphasized and these methods are compared on the basis of a dataset pertaining to metabolomics field.

引用

页码：214 / 235

页数：22

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