Papers by Giorgio Russolillo
plspm: Partial Least Squares Path Modeling (PLS-PM)
analysis of target genes Identification of microRNA-regulated gene networks by expression Material Supplemental
Partial least squares (PLS) refers to a set of iterative algorithms based on least squares that i... more Partial least squares (PLS) refers to a set of iterative algorithms based on least squares that implement a broad spectrum of both explanatory and exploratory multivariate techniques, from regression to path modeling, and from principal component to multi-block data analysis. This article focuses on PLS regression and PLS path modeling, which are PLS approaches to regularized regression and to predictive path modeling. The computational flows and the optimization criteria of these methods are reviewed in detail, as well as the tools for the assessment and interpretation of PLS models. The most recent developments and some of the most promising on going researches are enhanced.
Recherche et Applications en Marketing (French Edition), 2017
Notre ambition est de proposer un instrument multidimensionnel permettant de décrire le degré de ... more Notre ambition est de proposer un instrument multidimensionnel permettant de décrire le degré de présence des principales capacités marketing sur trois niveaux d’abstraction. Après avoir présenté le cadre théorique relatif aux capacités marketing, l’article souligne tout d’abord les limites des principales échelles proposées par Vorhies et al. (1999 ; 2009), Vorhies et Harker (2000), et Vorhies et Morgan (2003 ; 2005). Ensuite, les étapes nécessaires au développement et à la validation d’un index multidimensionnel formatif de troisième ordre sont détaillées. Sur la base d’une collecte de données réalisée auprès d’un échantillon de 199 PME françaises, la phase d’analyse de la validité convergente et discriminante de l’instrument est réalisée à l’aide de l’approche PLS aux modèles à variables latentes (PLS-PM). Enfin, la validité nomologique de l’instrument proposé est confirmée via l’étude de l’influence des capacités marketing sur la performance organisationnelle.
Recherche et Applications en Marketing (English Edition), 2018
We propose a multidimensional instrument to assess the degree of presence of marketing capabiliti... more We propose a multidimensional instrument to assess the degree of presence of marketing capabilities a firm possesses, at three levels of abstraction. We first present the theoretical framework for marketing capabilities and discuss the main scales proposed by Vorhies et al. Then, we detail the steps required to develop and validate our third-order formative instrument. We assess the convergent and discriminant validity of the proposed instrument via partial least squares path modelling (PLS-PM) applied to a sample of 199 French small- and medium-sized enterprises (SMEs). Finally, we check the nomological validity of our instrument by testing the positive effect of marketing capabilities on organisational performance.
Mots-clés: Analyse des données- data mining; Problèmes inverses et sparsité Résumé: L’approche PL... more Mots-clés: Analyse des données- data mining; Problèmes inverses et sparsité Résumé: L’approche PLS aux modèles à équations structurelles (PLS Path Modeling, PLS-PM) est couramment considérée comme une approche basée sur les composantes. Cette méthode a été récemment revisitée en tant que cadre général pour l’analyse des tableaux multiples. Nous proposons ici deux nouvelles méthodes d’estimation des poids externes dans le cadre de la PLS-PM: le Mode PLScore et le Mode PLScow. Chaque mode est fondé sur l’utilisation de la régression PLS pour l’étape d’estimation externe. Toutefois, en Mode PLScore une régression PLS est exécutée sous les contraintes classiques de la PLS-PM de variance unitaire pour les scores des variables latentes; tandis que dans le Mode PLScow les poids externes sont contraints d’avoir une norme unitaire. Cette dernière contrainte est la contrainte classique de normalisation dans le cadre de la régression PLS. Nous montrons comment les deux nouveaux modes sont liés...
MID1 Mutations in Patients With X-linked Opitz G/BBB Syndrome
This paper deals with robustness evaluation at station, and in particular for the train plat-form... more This paper deals with robustness evaluation at station, and in particular for the train plat-forming problem (TPP). This problem consists in a platform and route assignment in station for each scheduled train. A classical robustness evaluation is simulation: simulated delays are injected on arriving and departing trains then propagated, and results are averaged on a large number of trials. A robust solution of the TPP aims to limit the total amount of secondary delays. However, a simulation framework at station is difficult t o c alibrate: it requires a realistic delays generator and an accurate operating rules modeling. This paper proposes an original simulation framework using classical statistical learning algorithms and calibration assessment methods to model simulation inputs. This methodology is applied on delay data to simulate delay propagation at station. It highlights the importance of delay calibration by showing that even slight miscalibration of inputs can lead to stron...
Nowadays there is a pre-eminent need to measure very complex phenomena like poverty, progress, we... more Nowadays there is a pre-eminent need to measure very complex phenomena like poverty, progress, well-being, etc. As is well known, the main feature of a composite indicator is that it summarizes complex and multidimensional issues. Thanks to its features, Structural Equation Modeling seems to be a useful tool for building systems of composite indicators. Among the several methods that have been developed to estimate Structural Equation Models we focus on the PLS Path Modeling approach (PLS-PM), because of the key role that estimation of the latent variables (i.e. the composite indicators) plays in the estimation process. In this paper we provide a suite of statistical methodologies for handling categorical indicators with respect to the role they have in a system of composite indicators. A categorical variable can play an active or a moderating role. An active categorical variable directly participates in the construction of the model. In other words, it is a categorical indicator im...
The Multiple Facets of Partial Least Squares Methods
This volume presents state of the art theories, new developments, and important applications of P... more This volume presents state of the art theories, new developments, and important applications of Partial Least Square (PLS) methods. The text begins with the invited communications of current leaders in the field who cover the history of PLS, an overview of methodological issues, and recent advances in regression and multi-block approaches. The rest of the volume comprises selected, reviewed contributions from the 8th International Conference on Partial Least Squares and Related Methods held in Paris, France, on 26-28 May, 2014. They are organized in four coherent sections: 1) new developments in genomics and brain imaging, 2) new and alternative methods for multi-table and path analysis, 3) advances in partial least square regression (PLSR), and 4) partial least square path modeling (PLS-PM) breakthroughs and applications. PLS methods are very versatile methods that are now used in areas as diverse as engineering, life science, sociology, psychology, brain imaging, genomics, and bus...
After a presentation of the classical methodology of conjoint analysis we advocate the use of PLS... more After a presentation of the classical methodology of conjoint analysis we advocate the use of PLS regression instead of classical regression in order to obtain a better accuracy in the estimation of utilities. PLS regression provides also interesting graphical representations allowing quick and easy interpretation of the relations among preferences, attributes and profiles.
About the influence of quantification in PLS-PM for customer satisfaction
Ercim News, 2010
Due to the need to formalize models relating latent concepts, Partial Least Squares Path Modeling... more Due to the need to formalize models relating latent concepts, Partial Least Squares Path Modeling has been widely used in marketing research for the quantitative analysis of customer satisfaction. However, in marketing applications latent concepts are expressed as a synthesis of variables that cannot be measured strictu sensu. Typically, in fact, the consumer is asked to express the level of agreement to a statement, or a judgment about particular characteristics of the offered product or service, choosing one out of a set of ordered response levels. Variables observed in such a way, however, cannot be considered numerical, as they are not measured on an interval scale. Nearly always, in order to directly obtain quantitative values, the interviewer asks the interviewee to associate the agreement level to one of the values on a certain scale (e.g. 1-10 or 1-100). As a matter of fact, this procedure implies an a priori quantification of non-metric variables, which follows two rules: ...
On the use of Structural Equation Models and PLS Path Modeling to build composite indicators
Nowadays there is a pre-eminent need to measure very complex phenomena like poverty, progress, we... more Nowadays there is a pre-eminent need to measure very complex phenomena like poverty, progress, well-being, etc. As is well known, the main feature of a composite indicator is that it summarizes complex and multidimensional issues. Thanks to its features, Structural Equation Modeling seems to be a useful tool for building systems of composite indicators. Among the several methods that have been developed to estimate Structural Equation Models we focus on the PLS Path Modeling approach (PLS-PM), because of the key role that estimation of the latent variables (i.e. the composite indicators) plays in the estimation process. In this work, first we present Structural Equation Models and PLS-PM. Then we provide a suite of statistical methodologies for handling categorical indicators in PLS-PM. In particular, in order to take categorical indicators into account, we propose to use a modified version of the PLS-PM algorithm recently presented by Russolillo [2009]. This new approach provides a...
2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018
This paper presents an original methodology to estimate delay risk a few days before operations w... more This paper presents an original methodology to estimate delay risk a few days before operations with generalized linear models. These models represent a given variable with any distribution from the exponential family, allowing to compute for any subject its own probability distribution according to its features. This methodology is applied on small delays (less than 20 minutes) of high-speed trains arriving at a major french station. Several distributions are tested to fit delay data and three scenarios are evaluated: a single GLM with a negative binomial distribution and two two-part models using both a logistic regression as first part to compute the probability of arriving on time, and a second part using a negative binomial or a lognormal distribution to obtain the probabilities associated with positive delay values. This paper also proposes a validation methodology to assess the quality of these probabilistic prediction based on two aspects: calibration and discrimination.
Knowledge Extraction by Investigating Model Uncertainty through Predictive Path Modeling and Probabilistic Networks
A Joint Use of PLS Regression and PLS Path Modelling for a Data Analysis Approach to Latent Variable Modelling
Vincenzo Esposito Vinzi; Giorgio Russolillo; Laura Trinchera ESSEC Business School of Paris, Aven... more Vincenzo Esposito Vinzi; Giorgio Russolillo; Laura Trinchera ESSEC Business School of Paris, Avenue Bernard Hirsch B.P. 50105 Cergy-Pontoise 95021, France. Università degli Studi di Napoli \Federico II" Dipartimento di Matematica e Statistica Via Cintia Complesso Monte S. Angelo, Napoli 80126, Italy. Università degli Studi di Macerata Dipartimento di Studi sullo Sviluppo Economico Piazza Oberdan, 3, Macerata 62100, Italy. E-mail: vinzi@essec.fr; giorgio.russolillo@unina.it; laura.trinchera@unimc.it
We propose to use PLS path modeling to predict stressors requiring priority action from managers ... more We propose to use PLS path modeling to predict stressors requiring priority action from managers to reduce work-related stress of their company employees.
Modelling passenger train arrival delays with Generalized Linear Models and its perspective for scheduling at main stations
Integrated approaches for PLS Path Modeling: PLS regression Estimation Mode(l)s and Probabilistic Networks
L'approche PLS aux modeles a equations structurelles (PLS Path Modeling, PLS-PM) est couramme... more L'approche PLS aux modeles a equations structurelles (PLS Path Modeling, PLS-PM) est couramment consideree comme une approche basee sur les composantes. Cette methode a ete recemment revisitee en tant que cadre general pour l'analyse des tableaux multiples. Nous proposons ici deux nouvelles methodes d'estimation des poids externes dans le cadre de la PLS-PM: le Mode PLScore et le Mode PLScow. Chaque mode est fonde sur l'utilisation de la regression PLS pour l'etape d'estimation externe. Toutefois, en Mode PLScore une regression PLS est executee sous les contraintes classiques de la PLS-PM de variance unitaire pour les scores des variables latentes ; tandis que dans le Mode PLScow les poids externes sont contraints d'avoir une norme unitaire. Cette derniere contrainte est la contrainte classique de normalisation dans le cadre de la regression PLS. Nous montrons comment les deux nouveaux modes sont lies aux methodes d'estimation externe classiques de la...
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Papers by Giorgio Russolillo