本文選題：近似周期時間序列 + 周期識別及提取��； 參考：《華東師范大學》2015年碩士論文

【摘要】：對時間序列周期性的研究是現下研究的一個熱點.目前生活中的許多事件和現象,它們的歷史數據形成的時間序列存在一定的周期特征,但是有很多周期特征表現出周期長度不相等的現象.基于這方面的考慮,本文主要研究周期長度不固定的時間序列的周期性,即近似周期時間序列的周期識別及提取.本文首先介紹了近似周期時間序列的概念,對已被提出的基于矩估計方法提取時間變換函數做了簡單的介紹.并在此基礎上,提出了一種新的方法估計時間變換函數——擬合估計方法.對于擬合估計方法,擬合數據的提取非常重要,因此本文在第三章給出了兩種擬合數據的選取方法,并證明了第二種方法選取出的數據能夠真實的反映時間變換.最后將兩種估計時間變換函數的方法通過實證分析進行比較,說明了基于擬合估計方法得到的結果優(yōu)于基于矩估計方法得到的結果.本文最后指出一個現象,不同取樣方式對時間序列周期識別是有影響的.指出對于某些取樣方式,得到的時間序列的周期無法反映其真實周期.另外,由于時間序列噪聲的存在,本文給出的擬合數據選取方法在某些程度上會受到影響,還需要不斷改進.
[Abstract]:The research on the periodicity of time series is a hot topic.At present, many events and phenomena in life, the time series formed by their historical data have some periodic characteristics, but many of the periodic characteristics show the phenomenon that the period length is not equal.Based on these considerations, this paper mainly studies the periodicity of time series with unfixed cycle length, that is, the periodic identification and extraction of approximate periodic time series.In this paper, the concept of approximate periodic time series is introduced, and the time transform function extraction based on moment estimation is briefly introduced.On the basis of this, a new method for estimating time transform function-fitting estimation is proposed.For fitting estimation, the extraction of fitting data is very important, so this paper gives two methods of selecting fitting data in the third chapter, and proves that the data selected by the second method can truly reflect the time transformation.Finally, two methods of estimating time transform function are compared by empirical analysis, and the results based on fitting estimation method are better than those based on moment estimation method.Finally, this paper points out a phenomenon that different sampling methods have influence on time series period identification.It is pointed out that the period of time series can not reflect the true period for some sampling methods.In addition, due to the existence of time series noise, the fitting data selection method presented in this paper will be affected to some extent and needs to be improved.
【學位授予單位】：華東師范大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：O211.61

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本文編號：1744657