The author makes a stabilized and zero mean treatment of the statistic data on the per capita annual net income of henan farmers between 1978 and 2005 , and using the property of the autocorrelation function and partial autocorrelation function of time sequence , establishes the model appropriate for the data 摘要笔者根据河南省1978年2005年的农民人均纯收入统计数据,将这些数据进行平稳化、零均值化处理,并利用时间序列的自相关函数,偏自相关函数的性质,确认数据所适合的模型。
In time series analysis, the partial autocorrelation function (PACF) plays an important role in data analyses aimed at identifying the extent of the lag in an autoregressive model. The use of this function was introduced as part of the Box-Jenkins approach to time series modelling, where by plotting the partial autocorrelative functions one could determine the appropriate lags p in an AR(p) model or in an extended ARIMA(p,d,q) model.