Browsing by Author "Vilar, José"
Now showing items 1-19 of 19
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Analyzing categorical time series with the R package ctsfeatures
López-Oriona, Ángel; Vilar, José (Elsevier B.V., 2024-03)[Absctract]: Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with real-valued time series, categorical time series have received much less attention. However, the development of ... -
Bootstrap tests for nonparametric comparison of regression curves with dependent errors
Vilar, Juan M.; Vilar, José (Springer, 2007)In this paper, the problem of testing the equality of regression curves with dependent data is studied. Several methods based on nonparametric estimators of the regression function are described. In this setting, the ... -
Distributed classification based on distances between probability distributions in feature space
Montero Manso, Pablo; Morán-Fernández, Laura; Bolón-Canedo, Verónica; Vilar, José; Alonso-Betanzos, Amparo (Elsevier, 2019-09)[Abstract]: We consider a distributed framework where training and test samples drawn from the same distribution are available, with the training instances spread across disjoint nodes. In this setting, a novel learning ... -
F4: An All-Purpose Tool for Multivariate Time Series Classification
López-Oriona, Ángel; Vilar, José (MDPI, 2021)[Abstract] We propose Fast Forest of Flexible Features (F4), a novel approach for classifying multivariate time series, which is aimed to discriminate between underlying generating processes. This goal has barely been ... -
Hard and soft clustering of categorical time series based on two novel distances with an application to biological sequences
Lopez-Oriona, Ángel; Vilar, José; D'Urso, Pierpaolo (Elsevier, 2023)[Abstract]: Two novel distances between categorical time series are introduced. Both of them measure discrepancies between extracted features describing the underlying serial dependence patterns. One distance is based on ... -
Machine learning for multivariate time series with the R package mlmts
López-Oriona, Ángel; Vilar, José (Elsevier B.V., 2023-06)[Abstract]: Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with univariate time series, multivariate time series have typically received much less attention. However, the ... -
On the uniform strong consistency of local polynomial regression under dependence conditions
Francisco-Fernández, Mario; Vilar, Juan M.; Vilar, José (Taylor & Francis, 2003)[Abstract] In this paper, nonparametric estimators of the regression function, and its derivatives, obtained by means of weighted local polynomial fitting are studied. Consider the fixed regression model where the error ... -
Ordinal Time Series Analysis with the R Package otsfeatures
López-Oriona, Ángel; Vilar, José (MDPI, 2023-06)[Abstract] The 21st century has witnessed a growing interest in the analysis of time series data. While most of the literature on the topic deals with real-valued time series, ordinal time series have typically received ... -
Outlier Detection for Multivariate Time Series: A Functional Data Approach ®
López-Oriona, Ángel; Vilar, José (Elsevier, 2021)[Abstract] A method for detecting outlier samples in a multivariate time series dataset is proposed. It is assumed that an outlying series is characterized by having been generated from a different process than those ... -
Quantile Cross-Spectral Density: A Novel and Effective Tool for Clustering Multivariate Time Series
López-Oriona, Ángel; Vilar, José (Elsevier, 2021)[Abstract] Clustering of multivariate time series is a central problem in data mining with applications in many fields. Frequently, the clustering target is to identify groups of series generated by the same multivariate ... -
Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques
López-Oriona, Ángel; D'Urso, Pierpaolo; Vilar, José; Lafuente Rego, Borja Raúl (Elsevier, 2022-11)[Abstract]: Robust fuzzy clustering of multivariate time series is addressed when the clustering purpose is grouping together series generated from similar stochastic processes. Robustness to the presence of anomalous ... -
Quantile-Based Fuzzy Clustering of Multivariate Time Series in the Frequency Domain
López-Oriona, Ángel; Vilar, José; D'Urso, Pierpaolo (Elsevier, 2022)[Abstract] A novel procedure to perform fuzzy clustering of multivariate time series generated from different dependence models is proposed. Different amounts of dissimilarity between the generating models or changes on ... -
Recursive local polynomial regression under dependence conditions
Vilar, Juan M.; Vilar, José (Springer, 2000)In the case of the random design nonparametric regression, one recursive local polynomial smoother is considered. Expressions for the bias and the variance matrix of the estimators of the regression function and its ... -
Robust Methods for Soft Clustering of Multidimensional Time Series
López-Oriona, Ángel; D'Urso, Pierpaolo; Vilar, José; Lafuente Rego, Borja Raúl (MDPI, 2021)[Abstract] Three robust algorithms for clustering multidimensional time series from the perspective of underlying processes are proposed. The methods are robust extensions of a fuzzy C-means model based on estimates of the ... -
The Bootstrap for Testing the Equality of Two Multivariate Stochastic Processes with an Application to Financial Markets
López-Oriona, Ángel; Vilar, José (MDPI, 2022)[Abstract] The problem of testing the equality of generating processes of two multivariate time series is addressed in this work. To this end, we construct two tests based on a distance measure between stochastic processes. ... -
The bootstrap for testing the equality of two multivariate time series with an application to financial markets
Lopez-Oriona, Ángel; Vilar, José (Elsevier, 2022)[Abstract]: The problem of testing the equality of the generating processes of two multivariate time series is addressed in this work. To this aim, we construct four tests based on a distance measure between stochastic ... -
Two novel distances for ordinal time series and their application to fuzzy clustering
López-Oriona, Ángel; Weiß, Christian H.; Vilar, José (Elsevier B.V., 2023-09-30)[Abstract]: Time series clustering is a central machine learning task with applications in many fields. While the majority of the methods focus on real-valued time series, very few works consider series with discrete ... -
Unsupervised classification of categorical time series through innovative distances
López-Oriona, Ángel; Vilar, José; D'Urso, Pierpaolo (Avestia Publishing, 2022)[Abstract]: In this paper, two novel distances for nominal time series are introduced. Both of them are based on features describing the serial dependence patterns between each pair of categories. The first dissimilarity ... -
Unsupervised Classification of Categorical Time Series Through Innovative Distances
López-Oriona, Ángel; Vilar, José; D'Urso, Pierpaolo (Springer Science and Business Media Deutschland GmbH, 2023)[Abstract]: In this paper, two novel distances for nominal time series are introduced. Both of them are based on features describing the serial dependence patterns between each pair of categories. The first dissimilarity ...
