José Antonio
Vilar Fernández
Catedrático de Universidad
Publicaciones (70) Publicaciones de José Antonio Vilar Fernández
2024
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Analyzing categorical time series with the R package ctsfeatures
Journal of Computational Science, Vol. 76
2023
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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)
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Fuzzy Clustering Of Ordinal Time Series Based On Two Novel Distances
Proceedings of the International Conference on Statistics
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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
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Machine learning for multivariate time series with the R package mlmts
Neurocomputing, Vol. 537, pp. 210-235
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Ordinal Time Series Analysis with the R Package otsfeatures
Mathematics, Vol. 11, Núm. 11
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Two novel distances for ordinal time series and their application to fuzzy clustering
Fuzzy Sets and Systems, Vol. 468
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Unsupervised Classification of Categorical Time Series Through Innovative Distances
Studies in Classification, Data Analysis, and Knowledge Organization
2022
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Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques
International Journal of Approximate Reasoning, Vol. 150, pp. 55-82
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Quantile-based fuzzy clustering of multivariate time series in the frequency domain
Fuzzy Sets and Systems, Vol. 443, pp. 115-154
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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
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The Bootstrap for Testing the Equality of Two Multivariate Stochastic Processes with an Application to Financial Markets †
Engineering Proceedings, Vol. 18, Núm. 1
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The bootstrap for testing the equality of two multivariate time series with an application to financial markets
Information Sciences, Vol. 616, pp. 255-275
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Unsupervised Classification of Categorical Time Series through Innovative Distances
Proceedings of the International Conference on Statistics
2021
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A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach
BioSystems, Vol. 205
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Bootstrapping regression models with locally stationary disturbances
Test, Vol. 30, Núm. 2, pp. 341-363
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F4: An all-purpose tool for multivariate time series classification
Mathematics, Vol. 9, Núm. 23
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Outlier detection for multivariate time series: A functional data approach[Formula presented]
Knowledge-Based Systems, Vol. 233
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Quantile cross-spectral density: A novel and effective tool for clustering multivariate time series
Expert Systems with Applications, Vol. 185
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Robust Methods for Soft Clustering of Multidimensional Time Series †
Engineering Proceedings, Vol. 7, Núm. 1