Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques. - Ángel López-Oriona; Pierpaolo D'Urso; José Antonio Vilar; Borja R. Lafuente-Rego (CoRR, 2021)

Quantile cross-spectral density: A novel and effective tool for clustering multivariate time series. - Ángel López-Oriona; José Antonio Vilar (Expert Syst. Appl., 2021)

Outlier detection for multivariate time series: A functional data approach. - Ángel López-Oriona; José Antonio Vilar (Knowl. Based Syst., 2021)

Clustering of Time Series Based on Forecasting Performance of Global Models. - Ángel López-Oriona; Pablo Montero-Manso; José Antonio Vilar (AALTD@ECML/PKDD, 2022)

Quantile-based fuzzy clustering of multivariate time series in the frequency domain. - Ángel López-Oriona; José Antonio Vilar; Pierpaolo D'Urso (Fuzzy Sets Syst., 2022)

Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques. - Ángel López-Oriona; Pierpaolo D'Urso; José Antonio Vilar; Borja R. Lafuente-Rego (Int. J. Approx. Reason., 2022)

The bootstrap for testing the equality of two multivariate time series with an application to financial markets. - Ángel López-Oriona; José Antonio Vilar (Inf. Sci., 2022)

Spatial Weighted Robust Clustering of Multivariate Time Series Based on Quantile Dependence With an Application to Mobility During COVID-19 Pandemic. - Ángel López-Oriona; Pierpaolo D'Urso; José Antonio Vilar; Borja R. Lafuente-Rego (IEEE Trans. Fuzzy Syst., 2022)

Fuzzy clustering of ordinal time series based on two novel distances with economic applications. - Ángel López-Oriona; Christian Weiss; José Antonio Vilar (CoRR, 2023)

Ordinal time series analysis with the R package otsfeatures. - Ángel López-Oriona; José Antonio Vilar Fernández (CoRR, 2023)

Analyzing categorical time series with the R package ctsfeatures. - Ángel López-Oriona; José Antonio Vilar Fernández (CoRR, 2023)

Hard and soft clustering of categorical time series based on two novel distances with an application to biological sequences. - Ángel López-Oriona; José Antonio Vilar; Pierpaolo D'Urso (Inf. Sci., 2023)

Machine learning for multivariate time series with the R package mlmts. - Ángel López-Oriona; José Antonio Vilar (Neurocomputing, 2023)

Two novel distances for ordinal time series and their application to fuzzy clustering. - Ángel López-Oriona; Christian H. Weiß; José Antonio Vilar (Fuzzy Sets Syst., 2023)

Fuzzy clustering of circular time series based on a new dependence measure with applications to wind data. - Ángel López-Oriona; Ying Sun 002; Rosa M. Crujeiras (CoRR, 2024)

Analyzing categorical time series with the package ctsfeatures. - Ángel López-Oriona; José Antonio Vilar (J. Comput. Sci., 2024)

Time series clustering based on prediction accuracy of global forecasting models. - Ángel López-Oriona; Pablo Montero-Manso; José Antonio Vilar (Knowl. Based Syst., 2025)

Lag selection in feature-based clustering of time series. - Ángel López-Oriona; Ying Sun 002 (Knowl. Based Syst., 2025)

Erratum to "Spatial Weighted Robust Clustering of Multivariate Time Series Based on Quantile Dependence With an Application to Mobility During COVID-19 Pandemic". - Ángel López-Oriona; Pierpaolo D'Urso; José Antonio Vilar; Borja R. Lafuente-Rego (IEEE Trans. Fuzzy Syst., 2025)

Improving the prediction accuracy of statistical models: A new hierarchical clustering approach. - Ángel López-Oriona; Ying Sun 002; José Antonio Vilar (Stat. Comput., 2025)