【摘要】 时间序列模型是按照时间顺序取得的一系列数据。本文综合运用判别时间序列平稳性的方法,建立吉林省人均GDP的时间序列模型。在判别差分序列的平稳性之后,利用自相关和偏自相关图判别时间序列模型的自回归阶数(AR(P))和移动平均阶数(MA(q));然后利用SAS软件用CLS对时间序列模型的回归参数进行估计和显著性检验,并对通过检验的回归结果进行分析。更多还原

【Abstract】 The time series model defers a series of data which the time order obtains. This paper established time series model of Jilin Province’s GDP per capita using comprehensively the model of judging the stationaray time series process. After the stationary of difference series was identified, the autoregressive process of order p (AP(p))and moving average process of order q(MA(q))was identified through autocorrelation and partial autocorrelation fuctions graph. At last, the regressive parameters of time series model was estimated and testi- fied using SAS software by CLS approach, and the regressive results tested was analysed.更多还原