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Professor´s Information

Personal Data
Name   Vilar Fernández, Jose Antonio
Knowledge area   Estadística e investigación operativa
Faculty position   Catedrático de Universidad
Dedication   Total
E-mail   jose.vilarf@udc.es
Personal website   http://dm.udc.es/staff/jose_vilar
Research group   MODES

Location
Center Campus Phone Extension

Teaching
Degree(s) Course(s)
Grado en Biología Estadística
Grado en Ingeniería Informática Estadística

Published papers
  • Ángel López-Oriona, José A. Vilar, Pierpaolo D’Urso.
    Hard and soft clustering of categorical time series based on two novel distances with an application to biological sequences.
    Information Sciences, 624 (2023) , 467-492.

  • Ángel López-Oriona, José A. Vilar, Pierpaolo D'Urso, .
    Quantile-based fuzzy clustering of multivariate time series in the frequency domain.
    Fuzzy Sets and Systems, 443 (2022) , B , 115-154.

  • Ángel López-Oriona, José A. Vilar.
    The bootstrap for testing the equality of two multivariate time series with an application to financial markets.
    Information Sciences, 616 (2022) , 255-275.

  • Ángel López-Oriona, Pierpaolo D'Urso, José A. Vilar, Borja Lafuente-Rego.
    Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques.
    International Journal of Approximate Reasoning, 150 (2022) , 55-82.

  • Ángel López-Oriona, Pierpaolo D'Urso, José A. Vilar, Borja Lafuente-Rego.
    Spatial weighted robust clustering of multivariate time series based on quantile dependence with an application to mobility during COVID-19 pandemic.
    IEEE Transactions on Fuzzy Systems, 30 (2022) , 9 , 3990 - 4004.

  • Ángel López-Oriona, José A. Vilar.
    F4: An All-Purpose Tool for Multivariate Time Series Classification.
    Mathematics, 9 (2021) , 23 , 3051.

  • Jose Arturo Molina Mora, Pablo Montero-Manso, Raquel García-Batána, Rebeca Campos-Sánchez, Jose Vilar-Fernández, Fernando García.
    A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.
    Biosystems, 205 (2021) , 104411.

  • Elías Harrán, José Antonio Vilar Fernández, Lara Harrán Marengo.
    Sealing capacity of lateral canals with different root canal obturation techniques.
    Revista de la Asociación Odontológica Argentina, 109 (2021) , 1 , 9-19.

  • Guillermo Ferreira, Jorge Mateu, José A. Vilar, Joel Muñoz .
    Bootstrapping regression models with locally stationary disturbances.
    Test, 30 (2021) , 341-363.

  • Ángel López-Oriona, José A. Vilar.
    Outlier detection for multivariate time series: A functional data approach.
    Knowledge-Based Systems, 233 (2021) , 107527.

  • Ángel López-Oriona, José A. Vilar.
    Quantile cross-spectral density: A novel and effective tool for clustering multivariate time series.
    Expert Systems with Applications, 185 (2021) , 115677.

  • Lafuente-Rego B., D'Urso P., Vilar J.A.
    Robust fuzzy clustering based on quantile autocovariances.
    Statistical Papers, 61 (2020) , 2393-2448.

  • Vilar Jose A., Fernández-Casal Rubén, Fernández-Lozano Carlos.
    Covid-19 projections for Spain using forecast combinations.
    Boletín de Estadística e Investigación Operativa, 36 (2020) , 2 , 99-125.

  • Pablo Montero-Manso, Laura Morán-Fernández, Verónica Bolón-Canedo, José A.Vilar, Amparo Alonso-Betanzos.
    Distributed classification based on distances between probability distributions in feature space.
    Information Sciences, 496 (2019) , 431-450.

  • Two-sample homogeneity testing: A procedure based on comparing distributions of interpoint distances.
    Pablo Montero-Manso, José A. Vilar.
    Statistical Analysis and Data Mining: The ASA Data Science Journal, 12 (2019) , 3 , 234-252.

  • Dibben, N., Coutinho, E., Vilar, J.A., & Estévez-Pérez, G.
    Do Individual Differences Influence Moment-by-Moment Reports of Emotion Perceived in Music and Speech Prosody?.
    Frontiers in Behavioral Neuroscience, 12 (2018) , 184.

  • José A. Vilar, Borja Lafuente-Rego, Pierpaolo D’Urso.
    Quantile autocovariances: A powerful tool for hard and soft partitional clustering of time series.
    Fuzzy Sets and Systems, 340 (2018) , 38-72.

  • V. Tuset, M. Ferré, J. Otero-Ferrer, J.A. Vilar, B. Morales-Lin, A. Lombarte.
    Testing otolith morphology for measuring marine fish biodiversity.
    Marine & Freshwater Research, 67 (2016) , 7 , 1037-1048.

  • B. Lafuente-Rego, J. A. Vilar.
    Clustering of time series using quantile autocovariances.
    Advances in Data Analysis and Classification, 10 (2016) , 3 , 391-415.

  • M. García-Magariños, J. A. Vilar.
    A framework for dissimilarity-based partitioning clustering of categorical time series.
    Data Mining and Knowledge Discovery, 29 (2015) , 466-502.

  • A. Bode, M.G. Estévez, M. Varela, J.A. Vilar.
    Annual trend patterns of phytoplankton species abundance belie homogeneous taxonomical group responses to climate in the NE Atlantic upwelling.
    Marine Environmental Research, 110 (2015) , 81-91.

  • R. Ouréns, J. Freire, J. A. Vilar, L. Fernández.
    Influence of habitat and population density on recruitment and spatial dynamics of sea urchin Paracentrotus lividus in Galicia.
    ICES Journal of Marine Science, 71 (2014) , 5 , 1064-1072.

  • P. Montero, J. A. Vilar.
    TSclust: An R package for time series clustering.
    Journal of Statistical Software, 62 (2014) , 1 , 1 - 43.

  • J.A. Vilar, J. M. Vilar.
    Time series clustering based on nonparametric multidimensional forecast densities.
    Electronic Journal of Statistics, 7 (2013) , 1019-1046.

  • R. Cao, J. A. Vilar, J. M. Vilar, A. K. López.
    Sampling Error Estimation in Stratified Surveys.
    Open Journal of Statistics, 3 (2013) , 3 , 200-212.

  • M.G. Estévez Pérez, J. A. Vilar.
    Functional ANOVA starting from discrete data: an application to air quality data.
    Environmental and Ecological Statistics, 20 (2013) , 3 , 495-517.

  • J. M. Vilar, J. A. Vilar.
    A bootstrap test for the equality of non-parametric regression curves under dependence.
    Communications in Statistics / Theory and Methods, 41 (2012) , 6 , 1069-1088.

  • R. Cao, J. A. Vilar, J. M. Vilar.
    Generalized variance function estimation for binary variables in a large-scale sample survey.
    Australian and New Zealand Journal of Statistics, 54 (2012) , 3 , 301-324.

  • J.L. Relova, S. Pértega Dí­az, J.A. Vilar, E. López, M. Peleteiro y F. Ares.
    Effects of cell-phone radiation on the electroencephalographic spectra of epileptic patients.
    IEEE Antennas and Propagation Society, 52 (2010) , 6 , 173-179.

  • J. A. Vilar, A. M. Alonso, J. M. Vilar.
    Non-linear time series clustering based on non-parametric forecast densities.
    Computational Statistics and Data Analysis, 54 (2010) , 2850-2865.

  • S. Pértega Dí­az, J. A. Vilar.
    Comparing several parametric and nonparametric approaches to time series clustering: A simulation study.
    Journal of Classification, 27 (2010) , 3 , 333-362.

  • J. M. Vilar, J. A. Vilar, S. Pértega.
    Classifying time series data: A nonparametric approach.
    Journal of Classification, 0 (2009) , 26 , 3-28.

  • J. M. Vilar, J. A. Vilar, W. González .
    Bootstrap tests for nonparametric comparison of regression curves with dependent errors.
    Test, 16 (2007) , 1 , 123-145.

  • J. A. Vilar, S. Pértega.
    Discriminant and cluster analysis for Gaussian stationary processes: local linear fitting approach.
    Journal of Nonparametric Statistics, 16 (2004) , 443-462.

  • E. Harrán, J. A. Vilar.
    The Cemento-Dentino-Canal Junction, the Apical Foramen, and the Apical Constriction: Evaluation by Optical Microscopy.
    Journal of Endodontics, 29 (2003) , 3 , 214-219.

  • M. Francisco-Fernández, J. M. Vilar, J. A. Vilar.
    On the uniform strong consistency of local polynomial regression under dependence conditions.
    Communications in Statistics / Theory and Methods, 32 (2003) , 12 , 2441-2463.

  • J. M. Vilar, J. A. Vilar.
    Bootstrap of minimum distance estimators in regression with correlation disturbances.
    Journal of Statistical Planning and Inference, 108 (2002) , 283-299.

  • E. Herrán, C. Canalda, J. A. Vilar.
    Study of dentinal tubule architecture of permanent upper premolars: evaluation by SEM.
    Australian Endodontic Journal, 27 (2001) , 2 , 66-72.

  • J. M. Vilar, J. A. Vilar.
    Recursive local polynomial regression under dependence conditions.
    Test, 9 (2000) , 1 , 209-232.

  • J. A. Vilar, J. M. Vilar.
    Finite sample performance of density estimators from unequally spaced data.
    Statistics and Probability Letters, 50 (2000) , 63-73.

  • R. Muiño, L. Fernández, E. González-Gurriarán, J. Freire, J. A. Vilar.
    Size at maturity of Liocarcinus depurator (Brachyura: Portunidae): a reproductive and morphometric study.
    Journal of the Marine Biological Association of the United Kingdom, 79 (1999) , 295-303.

  • J. M. Vilar, J. A. Vilar.
    Recursive estimation of regresion functions by local polynomial fitting.
    Annals of the Institute of Statistical Mathematics, 50 (1998) , 4 , 729-754.