This paper presents a new methodology for clustering multivariate time series
leveraging optimal transport between copulas. Copulas are used to encode both
(i) intra-dependence of a multivariate time series, and (ii) inter-dependence
between two time series. Then, optimal copula transport allows us to define two
distances between multivariate time series: (i) one for measuring
intra-dependence dissimilarity, (ii) another one for measuring inter-dependence
dissimilarity based on a new multivariate dependence coefficient which is
robust to noise, deterministic, and which can target specified dependencies.
Description
[1509.08144] Optimal Copula Transport for Clustering Multivariate Time Series
%0 Journal Article
%1 marti2015optimal
%A Marti, Gautier
%A Nielsen, Frank
%A Donnat, Philippe
%D 2015
%K copulas optimal-transport
%T Optimal Copula Transport for Clustering Multivariate Time Series
%U http://arxiv.org/abs/1509.08144
%X This paper presents a new methodology for clustering multivariate time series
leveraging optimal transport between copulas. Copulas are used to encode both
(i) intra-dependence of a multivariate time series, and (ii) inter-dependence
between two time series. Then, optimal copula transport allows us to define two
distances between multivariate time series: (i) one for measuring
intra-dependence dissimilarity, (ii) another one for measuring inter-dependence
dissimilarity based on a new multivariate dependence coefficient which is
robust to noise, deterministic, and which can target specified dependencies.
@article{marti2015optimal,
abstract = {This paper presents a new methodology for clustering multivariate time series
leveraging optimal transport between copulas. Copulas are used to encode both
(i) intra-dependence of a multivariate time series, and (ii) inter-dependence
between two time series. Then, optimal copula transport allows us to define two
distances between multivariate time series: (i) one for measuring
intra-dependence dissimilarity, (ii) another one for measuring inter-dependence
dissimilarity based on a new multivariate dependence coefficient which is
robust to noise, deterministic, and which can target specified dependencies.},
added-at = {2019-12-11T14:36:06.000+0100},
author = {Marti, Gautier and Nielsen, Frank and Donnat, Philippe},
biburl = {https://www.bibsonomy.org/bibtex/2b6e7f65ca639c9704e844421f57cf430/kirk86},
description = {[1509.08144] Optimal Copula Transport for Clustering Multivariate Time Series},
interhash = {999d94733399ad8b3de5a81fb3d21587},
intrahash = {b6e7f65ca639c9704e844421f57cf430},
keywords = {copulas optimal-transport},
note = {cite arxiv:1509.08144Comment: Accepted at ICASSP 2016},
timestamp = {2019-12-11T14:36:06.000+0100},
title = {Optimal Copula Transport for Clustering Multivariate Time Series},
url = {http://arxiv.org/abs/1509.08144},
year = 2015
}