利用Kulback-Leibler散度改进自相关图
Improving the autodependogram using the Kulback-Leibler divergence
摘要：
自依赖图是最近在文献中提出的一种分析自依赖的图形设备。定义了计算经典的皮尔逊卡方统计量的独立性在各种滞后，以指出存在滞后依赖。本文提出了一个改进的图，通过替代卡方统计与估计的Kulback-Leibler分歧之间的二元密度的两个延迟变量和产品的边缘分布。一个模拟研究，良好的时间序列模型，表明这种新的autopendogram是更强大的比以前的。还示出了对财务数据的应用。
英文摘要：
The autodependogram is a graphical device recently proposed in the literature to analyze autodependencies. It is defined computing the classical Pearson chi-square statistics of independence at various lags in order to point out the presence lag-depedencies. This paper proposes an improvement of this diagram obtained by substituting the chi-square statistics with an estimator of the Kulback-Leibler divergence between the bivariate density of two delayed variables and the product of their marginal distributions. A simulation study, on well-established time series models, shows that this new autodependogram is more powerful than the previous one. An application to financial data is also shown.
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。
