On a black hole effect in bilinear curve resolution based on least squares

Vitale, Raffaele; Ruckebusch, Cyril

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.1002/cem.3442

URL permanente :

http://hdl.handle.net/20.500.12210/109645

Titre :

On a black hole effect in bilinear curve resolution based on least squares

Auteur(s) :

Vitale, Raffaele [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Ruckebusch, Cyril [Auteur]

Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516

Titre de la revue :

Journal of Chemometrics

Nom court de la revue :

J. Chemometr.

Numéro :

Pagination :

Date de publication :

2022-10-17

ISSN :

0886-9383

Mot(s)-clé(s) en anglais :

regression
leverage
least squares
curve resolution

Discipline(s) HAL :

Chimie/Chimie théorique et/ou physique

Résumé en anglais : [en]

Least squares-based estimations lay behind most chemometric methodologies. Their properties, though, have been extensively studied mainly in the domain of regression, in relation to which the effect of well-known deleterious ...
Lire la suite >Least squares-based estimations lay behind most chemometric methodologies. Their properties, though, have been extensively studied mainly in the domain of regression, in relation to which the effect of well-known deleterious factors (like object leverage or data distributions deviating from ideal conditions) on the accuracy of the prediction of an external response variable has been thoroughly assessed. Conversely, much less attention has been paid to what these factors might yield in alternative scenarios, where least squares approaches are still utilised, yet the objectives of data modelling may be very different. As an example, one can think of multivariate curve resolution (MCR) problems which are usually addressed by means of multivariate curve resolution-alternating least squares (MCR-ALS). In this respect, this article wants to offer a perspective on the basic principles of MCR-ALS from the regression point of view. In particular, the following critical aspects will be highlighted: (i) in the presence of minor components, if the number of analysed data points is too large, the leverage of those that may be essential for a MCR-ALS resolution might become too low for guaranteeing its correctness, and (ii) in order to overcome this black hole effect and improve the accuracy of the MCR-ALS output, data pruning can be exploited. More in detail, this communication will provide a practical illustration of such aspects in the field of hyperspectral imaging where even single experimental runs may lead to the generation of massive amounts of spectral recordings.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

Imagerie moléculaire active et sélective

Établissement(s) :

Université de Lille
CNRS

Collections :

Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516

Date de dépôt :

2024-02-28T23:44:07Z
2024-03-19T15:27:11Z

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Journal of Chemometrics - 2022 - Vitale - On a black hole effect in bilinear curve resolution based on least squares.pdf
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Ce document est diffusé sous licence Attribution-NonCommercial-NoDerivs 3.0 United States

Numéro de version	Lien	Date de modification
2	20.500.12210/109645*	2024-03-19T15:25:44Z
1	20.500.12210/109645.1	2024-02-28T23:44:07Z

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