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

机译:F. Battaglia和M. K. Protopapas讨论了“基于非线性非平稳时间序列模型的高山地区全球变暖分析”

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The paper by Battaglia and Protopapas (Stat Method Appl 2012) is stimulating. It gives an elegant mathematical generalization of autoregressive models (the nine types). It explains state-of-the-art model fitting techniques (genetic algorithm combined with fitness function and least squares). It is written in a fluent and authoritative manner. Important for having a wider impact: it is accessible to non-statisticians. Finally, it has interesting results on the temperature evolution over the instrumental period (roughly the past 200 years). These merits make this paper an important contribution to applied statistics as well as climatology. As a climate researcher, coming from Physics and having had an affiliation with a statistical institute only as postdoc, I re-analyse here three data series with the aim of providing motivation for model selection and interpreting the results from the climatological perspective.
机译:Battaglia和Protopapas的论文(Stat Method Appl 2012)令人振奋。它对自回归模型(九种类型)进行了优雅的数学概括。它解释了最新的模型拟合技术(结合了适应度函数和最小二乘的遗传算法)。它以流利,权威的方式编写。对于产生更大的影响很重要:非统计人员可以访问它。最后,它在仪器使用期间(大约过去200年)的温度变化方面产生了有趣的结果。这些优点使本文对应用统计和气候学做出了重要贡献。作为一名气候研究人员,他来自物理学,并且仅在博士后才与统计机构有隶属关系,在此我重新分析了三个数据系列,目的是为模型选择提供动力并从气候学角度解释结果。

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