Publicacións (70) Publicacións de José Antonio Vilar Fernández

2024

  1. Analyzing categorical time series with the R package ctsfeatures

    Journal of Computational Science, Vol. 76

2023

  1. Clustering of Time Series Based on Forecasting Performance of Global Models

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Fuzzy Clustering Of Ordinal Time Series Based On Two Novel Distances

    Proceedings of the International Conference on Statistics

  3. Hard and soft clustering of categorical time series based on two novel distances with an application to biological sequences

    Information Sciences, Vol. 624, pp. 467-492

  4. Machine learning for multivariate time series with the R package mlmts

    Neurocomputing, Vol. 537, pp. 210-235

  5. Ordinal Time Series Analysis with the R Package otsfeatures

    Mathematics, Vol. 11, Núm. 11

  6. Two novel distances for ordinal time series and their application to fuzzy clustering

    Fuzzy Sets and Systems, Vol. 468

  7. Unsupervised Classification of Categorical Time Series Through Innovative Distances

    Studies in Classification, Data Analysis, and Knowledge Organization

2022

  1. Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques

    International Journal of Approximate Reasoning, Vol. 150, pp. 55-82

  2. Quantile-based fuzzy clustering of multivariate time series in the frequency domain

    Fuzzy Sets and Systems, Vol. 443, pp. 115-154

  3. 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, Vol. 30, Núm. 9, pp. 3990-4004

  4. The Bootstrap for Testing the Equality of Two Multivariate Stochastic Processes with an Application to Financial Markets †

    Engineering Proceedings, Vol. 18, Núm. 1

  5. The bootstrap for testing the equality of two multivariate time series with an application to financial markets

    Information Sciences, Vol. 616, pp. 255-275

  6. Unsupervised Classification of Categorical Time Series through Innovative Distances

    Proceedings of the International Conference on Statistics

2021

  1. A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach

    BioSystems, Vol. 205

  2. Bootstrapping regression models with locally stationary disturbances

    Test, Vol. 30, Núm. 2, pp. 341-363

  3. F4: An all-purpose tool for multivariate time series classification

    Mathematics, Vol. 9, Núm. 23

  4. Outlier detection for multivariate time series: A functional data approach[Formula presented]

    Knowledge-Based Systems, Vol. 233

  5. Quantile cross-spectral density: A novel and effective tool for clustering multivariate time series

    Expert Systems with Applications, Vol. 185

  6. Robust Methods for Soft Clustering of Multidimensional Time Series †

    Engineering Proceedings, Vol. 7, Núm. 1