熵相关距离法用于研究富裕国家GDP之间的相关性
Entropy correlation distance method applied to study correlations between the Gross Domestic Product of rich countries
摘要：
泰尔指数在经济和金融中使用得很多;它看起来像香农熵，但与事件值有关，而不是与它们的概率有关。任何时间序列都可以通过Theil指数重新映射。相关系数可以在新的时间序列之间进行评估，从而允许研究它们的相互统计距离，-与主时间序列的通常相关距离度量形成对比。作为一个例子，这种熵的相关距离方法（ECDM）被应用到20个富裕国家的国内生产总值，以测试一些经济全球化进程。层次距离允许构造（i）线性网络，（ii）局部最小生成树。时间平均在有限大小的窗口中的作用进行了说明和讨论。它还表明，最发达国家之间的平均距离，从1960年到2000年一直在减少，我们认为这是这些国家经济全球化的证明。
英文摘要：
The Theil index is much used in economy and finance; it looks like the Shannon entropy, but pertains to event values rather than to their probabilities. Any time series can be remapped through the Theil index. Correlation coefficients can be evaluated between the new time series, thereby allowing to study their mutual statistical distance, - to be contrasted to the usual correlation distance measure for the primary time series. As an example this entropy-like correlation distance method (ECDM) is applied to the Gross Domestic Product of 20 rich countries in order to test some economy globalization process. Hierarchical distances allow to construct (i) a linear network, (ii) a Locally Minimal Spanning Tree. The role of time averaging in finite size windows is illustrated and discussed. It is also shown that the mean distance between the most developed countries, was decreasing since 1960 till 2000, - which we consider to be a proof of globalization of the economy for these countries.
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。
