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The bootstrap for testing the equality of two multivariate time series with an application to financial markets
(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 ...
Hard and soft clustering of categorical time series based on two novel distances with an application to biological sequences
(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 ...
Recursive local polynomial regression under dependence conditions
(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 ...
Bootstrap tests for nonparametric comparison of regression curves with dependent errors
(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 ...
On the uniform strong consistency of local polynomial regression under dependence conditions
(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 ...
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 ...
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 ...
Ordinal Time Series Analysis with the R Package otsfeatures
(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 ...
