Publication

On the added value of multiset methods for three-way data analysis

De Roover, K., Timmerman, M. E., Van Mechelen, I. & Ceulemans, E., 15-Nov-2013, In : Chemometrics and Intelligent Laboratory Systems. 129, p. 98-107 10 p.

Research output: Contribution to journalArticleAcademic

APA

De Roover, K., Timmerman, M. E., Van Mechelen, I., & Ceulemans, E. (2013). On the added value of multiset methods for three-way data analysis. Chemometrics and Intelligent Laboratory Systems, 129, 98-107. https://doi.org/10.1016/j.chemolab.2013.05.002

Author

De Roover, Kim ; Timmerman, Marieke E. ; Van Mechelen, Iven ; Ceulemans, Eva. / On the added value of multiset methods for three-way data analysis. In: Chemometrics and Intelligent Laboratory Systems. 2013 ; Vol. 129. pp. 98-107.

Harvard

De Roover, K, Timmerman, ME, Van Mechelen, I & Ceulemans, E 2013, 'On the added value of multiset methods for three-way data analysis', Chemometrics and Intelligent Laboratory Systems, vol. 129, pp. 98-107. https://doi.org/10.1016/j.chemolab.2013.05.002

Standard

On the added value of multiset methods for three-way data analysis. / De Roover, Kim; Timmerman, Marieke E.; Van Mechelen, Iven; Ceulemans, Eva.

In: Chemometrics and Intelligent Laboratory Systems, Vol. 129, 15.11.2013, p. 98-107.

Research output: Contribution to journalArticleAcademic

Vancouver

De Roover K, Timmerman ME, Van Mechelen I, Ceulemans E. On the added value of multiset methods for three-way data analysis. Chemometrics and Intelligent Laboratory Systems. 2013 Nov 15;129:98-107. https://doi.org/10.1016/j.chemolab.2013.05.002


BibTeX

@article{8e08a66c26d749f18b7646b484a43b7e,
title = "On the added value of multiset methods for three-way data analysis",
abstract = "Three-way three-mode data are collected regularly in scientific research and yield information on the relation between three sets of entities. To summarize the information in such data, three-way component methods like CANDECOMP/PARAFAC (CP) and Tucker3 are often used. When applying CP and Tucker3 in empirical practice, one should be cautious, however, because they rely on very strict assumptions. We argue that imposing these assumptions may obscure interesting structural information included in the data and may lead to substantive conclusions that are appropriate for some part of the data only. As a way out, this paper demonstrates that this structural information may be elegantly captured by means of component methods for multiset data, that is to say, simultaneous component analysis (SCA) and its clusterwise extension (clusterwise SCA). (C) 2013 Elsevier B.V. All rights reserved.",
keywords = "Three-way component analysis, Simultaneous component analysis, Clusterwise simultaneous component analysis, COMPONENT ANALYSIS, MODELS, CHULL",
author = "{De Roover}, Kim and Timmerman, {Marieke E.} and {Van Mechelen}, Iven and Eva Ceulemans",
year = "2013",
month = "11",
day = "15",
doi = "10.1016/j.chemolab.2013.05.002",
language = "English",
volume = "129",
pages = "98--107",
journal = "Chemometrics and Intelligent Laboratory Systems",
issn = "0169-7439",
publisher = "ELSEVIER SCIENCE BV",

}

RIS

TY - JOUR

T1 - On the added value of multiset methods for three-way data analysis

AU - De Roover, Kim

AU - Timmerman, Marieke E.

AU - Van Mechelen, Iven

AU - Ceulemans, Eva

PY - 2013/11/15

Y1 - 2013/11/15

N2 - Three-way three-mode data are collected regularly in scientific research and yield information on the relation between three sets of entities. To summarize the information in such data, three-way component methods like CANDECOMP/PARAFAC (CP) and Tucker3 are often used. When applying CP and Tucker3 in empirical practice, one should be cautious, however, because they rely on very strict assumptions. We argue that imposing these assumptions may obscure interesting structural information included in the data and may lead to substantive conclusions that are appropriate for some part of the data only. As a way out, this paper demonstrates that this structural information may be elegantly captured by means of component methods for multiset data, that is to say, simultaneous component analysis (SCA) and its clusterwise extension (clusterwise SCA). (C) 2013 Elsevier B.V. All rights reserved.

AB - Three-way three-mode data are collected regularly in scientific research and yield information on the relation between three sets of entities. To summarize the information in such data, three-way component methods like CANDECOMP/PARAFAC (CP) and Tucker3 are often used. When applying CP and Tucker3 in empirical practice, one should be cautious, however, because they rely on very strict assumptions. We argue that imposing these assumptions may obscure interesting structural information included in the data and may lead to substantive conclusions that are appropriate for some part of the data only. As a way out, this paper demonstrates that this structural information may be elegantly captured by means of component methods for multiset data, that is to say, simultaneous component analysis (SCA) and its clusterwise extension (clusterwise SCA). (C) 2013 Elsevier B.V. All rights reserved.

KW - Three-way component analysis

KW - Simultaneous component analysis

KW - Clusterwise simultaneous component analysis

KW - COMPONENT ANALYSIS

KW - MODELS

KW - CHULL

U2 - 10.1016/j.chemolab.2013.05.002

DO - 10.1016/j.chemolab.2013.05.002

M3 - Article

VL - 129

SP - 98

EP - 107

JO - Chemometrics and Intelligent Laboratory Systems

JF - Chemometrics and Intelligent Laboratory Systems

SN - 0169-7439

ER -

ID: 12300564