Table 5. ACF, PACF, and Ljung–Box test results for Korean red pine log time series at first differencing
| Lag | Autocorrelation (SE)1) | Partial autocorrelation (SE) | Box-Ljung statistic |
| Value | df | Sig.2) |
| 1 | –0.241 (0.248) | –0.241 (0.277) | 0.948 | 1 | 0.330 |
| 2 | –0.456 (0.238) | –0.546 (0.277) | 4.636 | 2 | 0.098 |
| 3 | 0.202 (0.226) | –0.151 (0.277) | 5.435 | 3 | 0.143 |
| 4 | 0.157 (0.215) | –0.096 (0.277) | 5.972 | 4 | 0.201 |
| 5 | –0.127 (0.203) | –0.048 (0.277) | 6.364 | 5 | 0.272 |
| 6 | –0.146 (0.189) | –0.190 (0.277) | 6.962 | 6 | 0.324 |
| 7 | 0.108 (0.175) | –0.109 (0.277) | 7.344 | 7 | 0.394 |
| 8 | 0.053 (0.160) | –0.138 (0.277) | 7.454 | 8 | 0.489 |
| 9 | 0.041 (0.143) | 0.093 (0.277) | 7.534 | 9 | 0.582 |
| 10 | –0.010 (0.124) | 0.106 (0.277) | 7.541 | 10 | 0.674 |
| 11 | –0.061 (0.101) | 0.083 (0.277) | 7.901 | 11 | 0.722 |
The null hypothesis assumes that the residuals are white noise (no autocorrelation).
Significance values (Sig.) are based on an asymptotic chi-square distribution.
ACF: autocorrelation function, PACF: partial autocorrelation function.