确定时间序列均值和方差函数的移动多点平均方法

王治华; 傅惠民; 张勇波

确定时间序列均值和方差函数的移动多点平均方法

北京航空航天大学小样本技术研究中心北京 100191

基金项目: 国家自然科学基金(11202011); 国家重点基础研究发展计划(2012CB720000); 凡舟青年科学基金(20100511)

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出版历程
- 收稿日期: 2012-08-28
- 刊出日期: 2012-11-28

Moving multi-point average method for determining functions of time series mean and variance

Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

摘要

摘要: 为了提高有限样本或小样本情况下时间序列均值和方差函数的确定精度,以保证时序建模、分析和预测精度,提出一种确定序列趋势项的移动多点平均方法.该方法能够得到时间序列均值中非周期部分,结合样本周期图法得到的周期项,可综合得到其均值函数,并可进一步得到时序的标准差函数.Monte Carlo模拟对比结果表明:该方法不仅能够保证时间序列段内分析精度,而且能够有效提高时间序列的预报精度.
- 时间序列 /
- 均值函数 /
- 方差函数 /
- 移动多点平均 /
- 预测
Abstract: A moving multiple-point average (MMPA) method was proposed to enhance the determining precision for time series mean and variance functions, and consequently to improve the accuracy for time series modeling, analyzing and forecasting. Non-periodic part of trend item which can be obtained by the MMPA approach, and the periodic part of trend item which can be calculated by sample periodogram method, comprise the whole trend function. We can further determine the series standard deviation function. Monte Carlo simulation study shows that not only the analysis precision but also the prediction accuracy can be ensured by the established methodology.
- time series /
- mean function /
- variance function /
- moving multi-point average /
- prediction

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参考文献(16)

[1]	Hamilton J D.Time series analysis [M].Princeton:Princeton University Press,1994.
[2]	Gujarati D.Essentials of econometrics[M].New York:McGraw Hill,1998.
[3]	罗开位,王晓刚.2003年度诺贝尔经济学奖评述[J].外国经济与管理,2003,25(11):34-38. LUO Kaiwei,WANG Xiaogang.Commentary on the Nobel economics prize in 2003[J].Foreign Economies and Management, 2003,25(11):34-38.(in Chinese)
[4]	Ibrahim A.Nonstationarity characteristics of the S&P500 returns:an approach based on the evolutionary spectral density[J].Economics Bulletin,2003,3(32):1-7.
[5]	Ibrahim A.A complementary test for the KPSS test with an application to the US Dollar/Euro exchange rate[J].Economics Bulletin,2004,3(4):1-5.
[6]	Loretan M,Phillips P C B.Testing the covariance stationarity of heavy-tailed time series: an overview of the theory with applications to several financial data sets[J].Journal of Empirical Finance,1994,1(2):211-248.
[7]	Mikosch T, Starica C.Change of structure in financial time series,long range dependence and the GARCH model [J].The Reviw Economics and Statistics,2004,86(1):378-390.
[8]	傅惠民.相关系数平稳过程[J].机械强度,2002,24(3):400-404. FU Huimin.Method for correlation coefficient stationary process[J].Journal of Mechanical Strength,2002,24(3):400-404.(in Chinese)
[9]	傅惠民,刘成瑞,马小兵.相关系数平稳过程时频分析方法[J].航空动力学报,2002,17(5):505-512. FU Huimin,LIU Chengrui,MA Xiaobing.Time frequency analysis of correlation coefficient stationary process[J].Journal of Aerospace Power, 2002,17(5):505-512.(in Chinese)
[10]	傅惠民,马小兵.相关系数MA(q)序列分析方法[J].机械强度,2003,25(2):183-186. FU Huimin,MA Xiaobing.Analysis method of correlation coefficient MA(q) series[J].Journal of Mechanical Strength,2003,25(2):183-186.(in Chinese)
[11]	傅惠民,刘成瑞,马小兵.相关系数ARMA(p,q)序列分析方法[J].航空动力学报,2003,18(2):161-166. FU Huimin,LIU Chengrui,MA Xiaobing.Analysis method of correlation coefficient ARMA(p, q) series[J].Journal of Aerospace Power,2003,18(2):161-166.(in Chinese)
[12]	傅惠民,王治华.广义时变ARMA模型参数函数的确定方法[J].机械强度,2004,26(6):636-641. FU Huimin,WANG Zhihua.Method for determining parametric functions of generalized time-varying ARMA model[J].Journal of Mechanical Strength,2004,26(6):636-641.(in Chinese)
[13]	王治华,傅惠民.广义时变ARMA序列预测方法[J].航空动力学报,2005,20(5):713-717. WANG Zhihua,FU Huimin.Prediction method for generalized time-varying ARMA series[J].Journal of Aerospace Power,2005,20(5):713-717.(in Chinese)
[14]	王治华,傅惠民.回归与时变自回归模型[J].机械强度,2005,27(5):612-615. WANG Zhihua,FU Huimin.Method of regression and time-varying autoregression[J].Journal of Mechanical Strength, 2005,27(5):612-615.(in Chinese)
[15]	王治华,傅惠民.时变序列分析方法[J].机械强度,2006,28(3):636-641. WANG Zhihua,FU Huimin.Method for time-varying series analysis[J].Journal of Mechanical Strength,2006,28(3):636-641.(in Chinese)
[16]	傅惠民,刘成瑞,马小兵.时间序列均值和方差函数的确定方法[J].机械强度,2004,26(2):164-169. FU Huimin,LIU Chengrui,MA Xiaobing.Method for determining functions of time series mean and variance[J].Journal of Mechanical Strength,2004,26(2):164-169.(in Chinese)