INGARCH-Based Fuzzy Clustering of Count Time Series with a Football Application

21 Pages Posted: 13 Jul 2022

See all articles by Roy Cerqueti

Roy Cerqueti

University Sapienza Rome

Pierpaolo D’Urso

Sapienza University of Rome

Livia De Giovanni

Luiss Guido Carli University

Raffaele Mattera

Sapienza University of Rome

Vincenzina Vitale

Sapienza University of Rome

Abstract

Although there are many contributions in the time series clustering literature, few studies still deal with count time series data. This paper aims to develop a fuzzy clustering procedure for count time series data. We propose an Integer GARCH-based Fuzzy C -medoids (INGARCH-FCMd) method for clustering count time series based on a Mahalanobis distance between the parameters estimated by an INGARCH model. We show how the proposed clustering method works by clustering football teams according to the number of scored goals.

Keywords: Fuzzy C-medoids, INGARCH, Poisson distribution, Sport analytics

Suggested Citation

Cerqueti, Roy and D’Urso, Pierpaolo and De Giovanni, Livia and Mattera, Raffaele and Vitale, Vincenzina, INGARCH-Based Fuzzy Clustering of Count Time Series with a Football Application. Available at SSRN: https://ssrn.com/abstract=4161563 or http://dx.doi.org/10.2139/ssrn.4161563

Roy Cerqueti

University Sapienza Rome ( email )

Piazzale Aldo Moro 5
Roma, Rome 00185
Italy

Pierpaolo D’Urso

Sapienza University of Rome ( email )

Livia De Giovanni (Contact Author)

Luiss Guido Carli University ( email )

Raffaele Mattera

Sapienza University of Rome ( email )

Vincenzina Vitale

Sapienza University of Rome ( email )

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