Buscar
Mostrando ítems 1-10 de 12
Outlier Detection for Multivariate Time Series: A Functional Data Approach ®
(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
(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 ...
Robust Methods for Soft Clustering of Multidimensional Time Series
(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 ...
F4: An All-Purpose Tool for Multivariate Time Series Classification
(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 ...
The Bootstrap for Testing the Equality of Two Multivariate Stochastic Processes with an Application to Financial Markets
(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. ...
Quantile-Based Fuzzy Clustering of Multivariate Time Series in the Frequency Domain
(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 ...
Machine learning for multivariate time series with the R package mlmts
(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 ...
Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques
(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 ...
Two novel distances for ordinal time series and their application to fuzzy clustering
(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
(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 ...