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Discussion of “An analysis of global warming in the Alpine region based of nonlinear nonstationary time series models” by F. Battaglia and M. K. Protopapas

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  • Domenico Piccolo

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    Abstract

    We discuss the scientific contribution of Battaglia and Protopapas’ paper concerning the debate on global warming supported by an extensive analysis of temperature time series in the Alpine region. In the work, Authors use several exploratory and modelling tools for assessing and discriminating the presence of different patterns in the data. We add some general and specific considerations mainly devoted to the modelling stage of their analysis. Copyright Springer-Verlag 2012

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    File URL: http://hdl.handle.net/10.1007/s10260-012-0203-6
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    Bibliographic Info

    Article provided by Springer in its journal Statistical Methods & Applications.

    Volume (Year): 21 (2012)
    Issue (Month): 3 (August)
    Pages: 363-369

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    Handle: RePEc:spr:stmapp:v:21:y:2012:i:3:p:363-369

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    Web page: http://link.springer.de/link/service/journals/10260/index.htm

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    Related research

    Keywords: ARIMA models; Time series classification; AR metric; Forecastability content; Non-linear models;

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    1. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
    2. Corduas, Marcella & Piccolo, Domenico, 2008. "Time series clustering and classification by the autoregressive metric," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1860-1872, January.
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