Saved in:
Bibliographic Details
Main Authors: Camacho, José, Ezenarro, Jokin, Schorn-García, Daniel, Westerhuis, Johan A.
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.19265
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911698148917248
author Camacho, José
Ezenarro, Jokin
Schorn-García, Daniel
Westerhuis, Johan A.
author_facet Camacho, José
Ezenarro, Jokin
Schorn-García, Daniel
Westerhuis, Johan A.
contents ANOVA Simultaneous Component Analysis (ASCA) is the current state-of-theart chemometric tool for analyzing and interpreting high-dimensional experimental data from a Design of Experiment (DoE). Being a multivariate extension of the ANOVA, ASCA makes a perfect tandem with DoE. This tutorial review recommends best practices for using ASCA, building upon the long-established combination of ANOVA and DoE theory developed over the last century. These recommendations are grounded in a comprehensive literature review and illustrated through a guiding example.
format Preprint
id arxiv_https___arxiv_org_abs_2604_19265
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From design of experiments to analysis of variance of multivariate data: a tutorial review on ANOVA simultaneous component analysis
Camacho, José
Ezenarro, Jokin
Schorn-García, Daniel
Westerhuis, Johan A.
Methodology
ANOVA Simultaneous Component Analysis (ASCA) is the current state-of-theart chemometric tool for analyzing and interpreting high-dimensional experimental data from a Design of Experiment (DoE). Being a multivariate extension of the ANOVA, ASCA makes a perfect tandem with DoE. This tutorial review recommends best practices for using ASCA, building upon the long-established combination of ANOVA and DoE theory developed over the last century. These recommendations are grounded in a comprehensive literature review and illustrated through a guiding example.
title From design of experiments to analysis of variance of multivariate data: a tutorial review on ANOVA simultaneous component analysis
topic Methodology
url https://arxiv.org/abs/2604.19265