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Publications

Publications by Paula Brito

2006

Organizational survival in cooperation networks: The case of automobile manufacturing

Authors
Campos, P; Brazdil, P; Brito, P;

Publication
Network-Centric Collaboration and Supporting Frameworks

Abstract
We propose a Multi-Agent framework to analyze the dynamics of organizational survival in cooperation networks. Firms can decide to cooperate horizontally (in the same market) or vertically with other firms that belong to the supply chain. Cooperation decisions are based on economic variables. We have defined a variant of the density dependence model to set up the dynamics of the survival in the simulation. To validate our model, we have used empirical outputs obtained in previous studies from the automobile manufacturing sector. We have observed that firms and networks proliferate in the regions with lower marginal costs, but new networks keep appearing and disappearing in regions with higher marginal costs.

2006

Dynamic clustering for interval data based on L-2 distance

Authors
de Carvalho, FDAT; Brito, P; Bock, HH;

Publication
COMPUTATIONAL STATISTICS

Abstract
This paper introduces a partitioning clustering method for objects described by interval data. It follows the dynamic clustering approach and uses an L-2 distance. Particular emphasis is put on the standardization problem where we propose and investigate three standardization techniques for interval-type variables. Moreover, various tools for cluster interpretation are presented and illustrated by simulated and real-case data.

2006

Linear discriminant analysis for interval data

Authors
Duarte Silva, APD; Brito, P;

Publication
COMPUTATIONAL STATISTICS

Abstract
This paper compares different approaches to the multivariate analysis of interval data, focusing on discriminant analysis. Three fundamental approaches are considered. The first approach assumes an uniform distribution in each observed interval, derives the corresponding measures of dispersion and association, and appropriately defines linear combinations of interval variables that maximize the usual discriminant criterion. The second approach expands the original data set into the set of all interval description vertices, and proceeds with a classical analysis of the expanded set. Finally, a third approach replaces each interval by a midpoint and range representation. Resulting representations, using intervals or single points, are discussed and distance based allocation rules are proposed. The three approaches are illustrated on a real data set.

1995

Symbolic objects: order structure and pyramidal clustering

Authors
Brito, P;

Publication
Annals OR

Abstract

2008

Preface

Authors
Brito, P; Figueiredo, A; Pires, A; Ferreira, AS; Marcelo, C; Figueiredo, F; Sousa, F; Da Costa, JP; Pereira, J; Torgo, L; Castro, LCE; Silva, ME; Milheiro, P; Teles, P; Campos, P; Silva, PD;

Publication
COMPSTAT 2008 - Proceedings in Computational Statistics, 18th Symposium

Abstract

2005

Structuring probabilistic data by Galois lattices

Authors
Brito, P; Polaillon, G;

Publication
Mathématiques et sciences humaines

Abstract

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