Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models

The class of threshold autoregressive models has been proven to be a powerful and appropriate tool to describe many dynamical phenomena in different fields. In this work, we deploy the threshold autoregressive moving-average framework to revisit the analysis of the benchmark Canadian lynx time serie...

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Main Author: Greta Goracci
Format: Article
Language:English
Published: University of Bologna 2021-03-01
Series:Statistica
Subjects:
Online Access:https://rivista-statistica.unibo.it/article/view/11478
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author Greta Goracci
author_facet Greta Goracci
author_sort Greta Goracci
collection DOAJ
description The class of threshold autoregressive models has been proven to be a powerful and appropriate tool to describe many dynamical phenomena in different fields. In this work, we deploy the threshold autoregressive moving-average framework to revisit the analysis of the benchmark Canadian lynx time series. This data set has attracted great attention among non-linear time series analysts due to its asymmetric cycle that makes the investigation very challenging. We compare some of the best threshold autoregressive models (TAR) proposed in literature with a selection of threshold autoregressive moving-average models (TARMA). The models are compared under different prospectives: (i) goodness-of-fit through information criteria, (ii) their ability to reproduce characteristic cycles, (iv) their capability to capture multimodality and (iii) forecasting performance. We found TARMAmodels that perform better than TAR models with respect to all these aspects.
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spelling doaj.art-3dd78340d06644fe9dda88f11c36ebc82022-12-21T22:45:08ZengUniversity of BolognaStatistica0390-590X1973-22012021-03-0180435739410.6092/issn.1973-2201/114789804Revisiting the Canadian Lynx Time Series Analysis Through TARMA ModelsGreta Goracci0 University of BolognaThe class of threshold autoregressive models has been proven to be a powerful and appropriate tool to describe many dynamical phenomena in different fields. In this work, we deploy the threshold autoregressive moving-average framework to revisit the analysis of the benchmark Canadian lynx time series. This data set has attracted great attention among non-linear time series analysts due to its asymmetric cycle that makes the investigation very challenging. We compare some of the best threshold autoregressive models (TAR) proposed in literature with a selection of threshold autoregressive moving-average models (TARMA). The models are compared under different prospectives: (i) goodness-of-fit through information criteria, (ii) their ability to reproduce characteristic cycles, (iv) their capability to capture multimodality and (iii) forecasting performance. We found TARMAmodels that perform better than TAR models with respect to all these aspects.https://rivista-statistica.unibo.it/article/view/11478population dynamicspredator-prey interactioncanadian lynx time seriesnonlinear time seriestarma processesasymmetric cycle
spellingShingle Greta Goracci
Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models
Statistica
population dynamics
predator-prey interaction
canadian lynx time series
nonlinear time series
tarma processes
asymmetric cycle
title Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models
title_full Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models
title_fullStr Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models
title_full_unstemmed Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models
title_short Revisiting the Canadian Lynx Time Series Analysis Through TARMA Models
title_sort revisiting the canadian lynx time series analysis through tarma models
topic population dynamics
predator-prey interaction
canadian lynx time series
nonlinear time series
tarma processes
asymmetric cycle
url https://rivista-statistica.unibo.it/article/view/11478
work_keys_str_mv AT gretagoracci revisitingthecanadianlynxtimeseriesanalysisthroughtarmamodels