Cluster analysis of time series via Kendall distribution

Fabrizio Durante; Roberta Pappadà

doi:10.1007/978-3-319-10765-3_25

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Cluster analysis of time series via Kendall distribution

Book chapter

Peer reviewed

Cluster analysis of time series via Kendall distribution

Fabrizio Durante and Roberta Pappadà

Strengthening Links Between Data Analysis and Soft Computing, pp.209-216

Advances in Intelligent Systems and Computing, Springer

2015

DOI: https://doi.org/10.1007/978-3-319-10765-3_25

Handle:

https://hdl.handle.net/10863/10543

Abstract

Quantitative methods and economic modeling

Copulas

Clustering methods

Dependence models

We present a method to cluster time series according to the calculation of the pairwise Kendall distribution function between them. A case study with environmental data illustrates the introduced methodology.

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Details

Title: Cluster analysis of time series via Kendall distribution
Creators: Fabrizio Durante
Roberta Pappadà
Publication Details: Strengthening Links Between Data Analysis and Soft Computing, pp.209-216
Editor(s): Grzegorzewski P, Gagolewski M, Hryniewicz O, Gil MA
ISBN: 978-3-319-10764-6
EISBN: 978-3-319-10765-3
ISSN: 2194-5357
EISSN: 2194-5365
Series / Volume: Advances in Intelligent Systems and Computing
Publisher: Springer
Cham
Number of pages: 8
Identifiers: 978-3-319-10764-6
(UNIBZ)1136120
991005772827101241
Web of Science ID: 000347613100025
Scopus ID: 2-s2.0-84921364357
Academic Unit: Faculty of Economics and Management
Language: English
Resource Type: Book chapter
Author Names String: Durante F, Pappadà R
Additional Description: srcEditors: Grzegorzewski P, Gagolewski M, Hryniewicz O, Gil MA
Projected: 3339
unibz-area: Quantitative methods and economic modeling
ERC: Statistics
ERCCODE: PE1_14
MIURSSD: Statistica
MIURSSDCODE: SECS-S/01

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