然後檢測自我相關性的部分，我們可以看到，各自變數之間都沒有共線性的問題

然後檢測自我相關性的部分，我們可以看到，各自變數之間都沒有共線性的問題，除了進口及出口比率之間相關性達到0.8，但需要刪除變數程度是在+-0.9以上，所以為了保持模型的完整性，我們選擇不刪除任何變數來對整體資料進行分析及預測

結果 (英文) 1:

And then detecting the correlation part of ourselves, we can see that no collinearity problems between each variable, except the ratio between import and export correlation of 0.8, but the need to remove the variable degree is + -0.9 or more, so in order to to maintain the integrity of the model, we choose not to remove any variables to analyze and forecast the overall data

結果 (英文) 2:

Then to detect the self-correlation part, we can see that there is no collinearity between the respective variables, except for the correlation between the import and export ratios reached 0.8, but the degree of removal of variables is above .0.9, so in order to maintain the integrity of the model, We choose not to delete any variables to analyze and forecast the overall data

結果 (英文) 3:

Then we can see that there is no problem of collinearity between the variables. Except that the correlation between import and export reaches 0.8, but the degree of variables to be deleted is above + - 0.9. So in order to maintain the integrity of the model, we choose not to delete any variables to analyze and predict the overall data