【摘要】 应用BDS统计量分析方法以及Lyapunov指数的分析方法研究经济时间序列的随机特性、混沌特性,应用R/S分析方法研究时间序列短期或长期依赖特性及其演化趋势,从而进一步探明时序所对应的系统的内在复杂性本质,为时序的建模提供理论依据.通过对3组不同的经济时序进行的实证研究,研究结果对于实测的经济时序内在本质特征的判定,有较为重要的理论和实际意义,为进一步寻找适合的非线性模型对经济时间序列进行有效分析和预测提供了理论依据.更多还原

【Abstract】 Applying the BDS statistics to measure analysis method and the Lyapunov exponent analysis method, we study the machine characteristic and mentally dense characteristic of economic time series. Applying the R/ S analysis method, we study the depending characteristic about the short-term or long-term time series and its evolvement trend. Consequently, we explore the inside complexity essential characteristics of the system of time series, which provides the theories groundwork for time serial molding. With the study on three different substantial evidences for economic time series, the research result has the important theories and actual meaning for the judgment about the essential characteristics of the solid economic time serial. It provides the theories groundwork for finding further valid analysis and forecast method about economic time series.更多还原