多尺度关系建模的EMD回归及其在天气相关心血管死亡率中的应用
EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality
摘要：
在一些环境研究中，自然过程之间的关系往往是通过回归分析，利用时间序列数据来评估的。这些数据通常是多尺度和非平稳的，导致所得回归模型的准确性较差，因此得出的结果具有中等可靠性。为了解决这个问题，本文介绍了经验模态分解（EMD）算法的数据序列，然后使用回归模型中产生的组件组成的EMD回归方法。所提议的方法具有若干优点。首先，它说明了与数据系列相关的非平稳性问题。其次，这种方法可以扫描不同时间尺度下的响应变量和预测变量之间的关系，为这种关系提供新的见解。为了说明所提出的方法，它适用于研究天气和心血管疾病死亡率之间的关系在加拿大蒙特利尔。结果揭示了新的知识，有关的研究关系。例如，他们表明，湿度可以在月时间尺度上导致过量的死亡率，这是一个在经典模型中不可见的尺度。还进行了比较与最先进的方法，这是广义可加模型和分布滞后模型，这两个广泛使用的天气相关的健康研究。比较表明，EMD回归实现了更好的预测性能，并提供了更多的细节比经典模型的关系。
英文摘要：
In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
