用ACF和PACF来确定arma模型中的p/q 值,到底要如何判断:
如以下结构,如何判断选用AR模型,还是MA模型,还是ARIMA模型,还有p/q值。请大侠指点。
MODEL: MOD_2.
Variable: GDP_1 Missing cases: 1 Valid cases: 36
Autocorrelations: GDP_1 DIFF(GDP,1)
Auto- Stand.
Lag Corr. Err. -1 -.75 -.5 -.25 0 .25 .5 .75 1 Box-Ljung Prob.
蝌螋蝌蝌趄蝌螋蝌蝌趄蝌螋蝌蝌趄蝌螋蝌蝌?
1 .720 .160 . ?****.******** 20.248 .000
2 .715 .158 . ?****.******** 40.829 .000
3 .542 .155 . ?****.***** 52.995 .000
4 .443 .153 . ?****.*** 61.384 .000
5 .358 .151 . ?****.* 67.042 .000
6 .301 .148 . ?***** 71.174 .000
7 .230 .146 . ?****. 73.660 .000
8 .110 .143 . ?* . 74.251 .000
9 .053 .140 . ? . 74.394 .000
10 -.016 .138 . * . 74.407 .000
11 -.052 .135 . *? . 74.556 .000
12 -.110 .132 . **? . 75.243 .000
13 -.106 .130 . **? . 75.912 .000
14 -.160 .127 . ***? . 77.502 .000
15 -.217 .124 .****? . 80.559 .000
16 -.178 .121 .****? . 82.734 .000
Plot Symbols: Autocorrelations * Two Standard Error Limits .
Total cases: 37 Computable first lags: 35
Partial Autocorrelations: GDP_1 DIFF(GDP,1)
Pr-Aut- Stand.
Lag Corr. Err. -1 -.75 -.5 -.25 0 .25 .5 .75 1
蝌螋蝌蝌趄蝌螋蝌蝌趄蝌螋蝌蝌趄蝌螋蝌蝌?
1 .720 .167 . ?*****.*******
2 .409 .167 . ?*****.*
3 -.142 .167 . ***? .
4 -.134 .167 . ***? .
5 .040 .167 . ? .
6 .076 .167 . ?* .
7 -.051 .167 . *? .
8 -.238 .167 . *****? .
9 -.036 .167 . *? .
10 .084 .167 . ?* .
11 .015 .167 . * .
12 -.144 .167 . ***? .
13 .019 .167 . * .
14 .008 .167 . * .
15 -.157 .167 . ***? .
16 .100 .167 . ?* .
Plot Symbols: Autocorrelations * Two Standard Error Limits .
Total cases: 37 Computable first lags: 35


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