In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The main features of this package is the possibility to take into account different types of variables (quantitative or categorical), different types of structure on the data (a partition on the variables, a hierarchy on the variables, a partition on the individuals) and finally supplementary information (supplementary individuals and variables). Moreover, the dimensions issued from the different exploratory data analyses can be automatically described by quantitative and/or categorical variables. Numerous graphics are also available with various options. Finally, a graphical user interface is implemented within the Rcmdr environment in order to propose an user friendly package.

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FactoMineR: An R Package for Multivariate Analysis

Principal component analysis PCA is a multivariate technique that analyzes a data table in which observations are described by several inter-correlated quantitative dependent variables. Its goal is to extract the important information from the table, to represent it as a set of new orthogonal variables called principal components, and to display the pattern of similarity of the observations and of the variables as points in maps. The quality of the PCA model can be evaluated using cross-validation techniques such as the bootstrap and the jackknife. PCA can be generalized as correspondence analysis CA in order to handle qualitative variables and as multiple factor analysis MFA in order to handle heterogeneous sets of variables. Mathematically, PCA depends upon the eigen-decomposition of positive semi-definite matrices and upon the singular value decomposition SVD of rectangular matrices. Copyright © 2010 John Wiley & Sons, Inc.

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Principal component analysis

Monographs on statistics and applied probability

Clustering is the partitioning of a set of objects into groups (clusters) so that objects within a group are more similar to each others than objects in different groups. Most of the clustering algorithms depend on some assumptions in order to define the subgroups present in a data set. As a consequence, the resulting clustering scheme requires some sort of evaluation as regards its validity.
The evaluation procedure has to tackle difficult problems such as the quality of clusters, the degree with which a clustering scheme fits a specific data set and the optimal number of clusters in a partitioning. In the literature, a wide variety of indices have been proposed to find the optimal number of clusters in a partitioning of a data set during the clustering process. However, for most of indices proposed in the literature, programs are unavailable to test these indices and compare them.
The R package NbClust has been developed for that purpose. It provides 30 indices which determine the number of clusters in a data set and it offers also the best clustering scheme from different results to the user. In addition, it provides a function to perform k-means and hierarchical clustering with different distance measures and aggregation methods. Any combination of validation indices and clustering methods can be requested in a single function call. This enables the user to simultaneously evaluate several clustering schemes while varying the number of clusters, to help determining the most appropriate number of clusters for the data set of interest.

NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set

This book considers why institutional forms of modern capitalist economies differ internationally, and proposes a typology of capitalism based on the theory of institutional complementarity Different economic models are not simply characterized by different institutional forms, but also by particular patterns of interaction between complementary institutions which are the core characteristics of these models Institutions are not just simply devices which would be chosen by 'social engineers' in order to perform a function as efficiently as possible; they are the outcome of a political economy process Therefore, institutional change should be envisaged not as a move towards a hypothetical 'one best way', but as a result of socio-political compromises Based on a theory of institutions and comparative capitalism, the book proposes an analysis of the diversity of modern economies - from America to Korea - and identifies five different models: the market-based Anglo-Saxon model; Asian capitalism; the Continental European model; the social democratic economies; and the Mediterranean model Each of these types of capitalism is characterized by specific institutional complementarities The question of the stability of the Continental European model of capitalism has been open since the beginning of the 1990s: inferior macroeconomic performance compared to Anglo-Saxon economies, alleged unsustainability of its welfare systems, too rigid markets, etc The book examines the institutional transformations that have taken place within Continental European economies and analyses the political project behind the attempts at transforming the Continental model It argues that Continental European economies will most likely stay very different from the market-based economies, and caat political strategies promoting institutional change aiming at convergence with the Anglo-Saxon model are bound to meet considerable opposition

The Diversity of Modern Capitalism

In the framework of the JuriSent case study, carried out within the European NEMIS thematic network, we analyze the contribution of text mining techniques to improve the consultation of jurisprudence textual databases. We mainly focus on correspondence analysis (CA) techniques, but also provide some insights on similar visualization techniques, such as self organizing maps (Kohonen maps), and review the potential impact of various Natural Language pre-processing techniques. CA is described in more detail, as well as its use in all the steps of the analysis. A concrete example is provided to illustrate the value of the results obtained with CA techniques for an enhanced access to the studied jurisprudence corpus.

Extraction of the Useful Words from a Decisional Corpus. Contribution of Correspondence Analysis

© Les cahiers de l’analyse des données, Dunod, 1981, tous droits réservés. L’accès aux archives de la revue « Les cahiers de l’analyse des données » implique l’accord avec les conditions générales d’utilisation (http: //www.numdam.org/conditions). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright.

Une procédure d'analyse lexicale écrite en langage FORTRAN

This paper aims at highlighting the contribution of both exploratory multivariate methods and textual analysis to the assessment of data quality in surveys.
The basic idea is that each step in carrying out a survey, from the conception of the questionnaire to the very end of the interview, can provide us with a series of control variables. These variables could be numerical (e.g. circumstances, location of the interview) or textual (e.g. open ended questions about the content of the survey).
The methods mentioned above allow for confrontations of initial data files and the control file, leading to an assessment of the obtained information.

Qualité de l'information dans les enquêtes

Dynamic Context Matching for Knowledge Acquisition from Small Corpora

In the domain of text analysis, a large spectrum of statistical methods has been developed in order to solve problems such as authorship attribution, time determination, information retrieval, processing of responses to open questions in surveys. In analyses of this kind, the applied statistical methods have to produce discrimination models. The textual data entities may be chosen by features of form, or by characteristics of content.

Ludovic Lebart

Papers

Extraction of the Useful Words from a Decisional Corpus. Contribution of Correspondence Analysis

Une procédure d'analyse lexicale écrite en langage FORTRAN

Qualité de l'information dans les enquêtes

Dynamic Context Matching for Knowledge Acquisition from Small Corpora

Discriminant Analysis Using Textual Data