Multidimensional Scaling Visualization Using Parametric Similarity Indices

• Tipo: Artigo em Revista Científica Internacional
• Data: 2015

Autores

Tenreiro Machado, JAT (Autor) Outra; António Mendes Lopes (Autor) FEUP; Galhano, AM (Autor) Outra

Revista

Título: Entropy

Vol. 17

Páginas: 1775-1794

ISSN: 1099-4300

Editora: MDPI

Indexação

ISI Web of Knowledge - 39 Citações

Scopus - 43 Citações

Outras Informações

ID Authenticus: P-00G-49A

DOI: 10.3390/e17041775

Abstract (EN): In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of 'points'. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of "shapes". This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 20