Persona:
Matilla García, Mariano

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ORCID
0000-0002-6007-3522
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Matilla García
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Mariano
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2017 - 20192
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Fecha de finalización: 2019 × search.filters.applied.f.itemDepartamento: Economía Aplicada y Estadística ×

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Mostrando 1 - 2 de 2
  • Miniatura
    Publicación
    A test for deterministic dynamics in spatial processes
    (2019-01-19) García-Córdoba, Jose A.; Matilla García, Mariano; Ruiz Marín, Manuel
    We propose a statistical procedure to determine if a spatial structure that is observed in the data is generated by a deterministic (even chaotic) spatial process, rather than by a stochastic process. This procedure can be used as a specification test. It is robust against nonlinearity and nonstationarity and can complete the toolbox for testing diagnosis as well. The advantages of the presented methods are high power, simplicity, and ease and ample applicability for tests to be conducted, provided that weak conditions are required. Herein, we conduct several simulations to evaluate the performance of our procedure on well-known spatial processes and in situations where standard tests for spatial autocorrelation fail to detect spatial dependence. Guidelines for using the technique are also provided herein.
  • Miniatura
    Publicación
    Symbolic correlation integral
    (0747-4938; eISSN: 1532-4168, 2017-09-26) Caballero Pintado, María Victoria; Matilla-García, M; Ruís Marín, Manuel; Matilla García, Mariano
    This paper aims to introduce the concept of symbolic correlation integral SC that is extensively used in many scientific fields. The new correlation integral SC avoids the noisy parameter 𝜀 of the classical correlation integral, defined by Grassberger and Procaccia (Citation1983) and extensively used for constructing correlation-integral-based statistics, as in the BDS test. Once the free parameter 𝜀 disappears, it is possible to construct a nonparametric powerful test for independence that can also be used as a diagnostic tool for model selection. The symbolic correlation integral is also extended to deal with multivariate models, and a test for causality is proposed as an example of the theoretical power of the new concept. With extensive Monte Carlo simulations, the paper shows the good size and power performance of symbolic correlation-integral-based tests.