Borja Lafuente-Rego

Quantile autocovariances: A powerful tool for hard and soft partitional clustering of time series

José A. Vilar, Borja Lafuente-Rego, Pierpaolo D’Urso · Fuzzy Sets and Systems · 2017 · 47 citations

Engineering, Data Science, Quantile Autocovariances +5

Clustering of time series using quantile autocovariances

Borja Lafuente-Rego, José A. Vilar · Advances in Data Analysis and Classification · 2015 · 40 citations

Statistics, Nonlinear Time Series, Temporal Pattern Recognition

Robust fuzzy clustering based on quantile autocovariances

Borja Lafuente-Rego, Pierpaolo D’Urso, José A. Vilar · Statistical Papers · 2018 · 32 citations · Full text

Fuzzy Logic, Engineering, Fuzzy Clustering +5

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

Ángel López‐Oriona, Pierpaolo D’Urso, José A. Vilar et al. · International Journal of Approximate Reasoning · 2022 · 31 citations · Full text

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 A. Vilar et al. · IEEE Transactions on Fuzzy Systems · 2021 · 20 citations

Engineering, Spatio-temporal Model, Quantile Dependence +16