本文選題：時間序列 + 平穩(wěn)性�。� 參考：《統(tǒng)計與決策》2017年17期

【摘要】：Box-Pierce Q檢驗采用近似卡方分布分析時間序列的平穩(wěn)性特征,其檢驗統(tǒng)計量的參數(shù)選取將影響到檢驗結(jié)果。文章多個Q值提取平穩(wěn)性特征,在此基礎(chǔ)上建立新的平穩(wěn)性判定準則,該準則是自相關(guān)函數(shù)序列收斂的充分條件;采用歐氏函數(shù)作為平穩(wěn)性特征的相似性度量,借助k-means聚類建立平穩(wěn)性分類方法;該方法在平穩(wěn)性分析過程中充分考慮了樣本之間的關(guān)聯(lián)性,避免了傳統(tǒng)Box-Pierce Q檢驗對統(tǒng)計分布和臨界表的過度依賴。實驗結(jié)果表明,新方法能有效地處理海量時間序列數(shù)據(jù),且準確率高于Q檢驗和ADF檢驗。
[Abstract]:The Box-Pierce Q test uses approximate chi-square distribution to analyze the stationary characteristics of time series, and the parameters of the test statistics will affect the test results.In this paper, several Q values are used to extract stationary features, and a new stationary criterion is established, which is a sufficient condition for the convergence of autocorrelation function sequences, and Euclidean function is used as the similarity measure of stationary features.The stationary classification method is established by means of k-means clustering, which takes full account of the correlation between samples in the stationary analysis process, and avoids the over-dependence of the traditional Box-Pierce Q test on the statistical distribution and critical table.The experimental results show that the new method can deal with massive time series data effectively, and the accuracy is higher than that of Q test and ADF test.
【作者單位】： 南華大學經(jīng)濟管理學院;
【基金】：教育部人文社科青年項目(13YJCZH044)
【分類號】：O211.61

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1 曾慶武;;滬深兩市股指平穩(wěn)性研究[J];運城學院學報;2005年S1期

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本文編號：1761961