Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China

Table 6

Quadratic function regression results of road transportation economic cost.

Dependent variable: Y
Method: least squares
Date: 01/26/21 time: 16 : 19
Sample: 1 83
Included observations: 83
Y = C(1)∗X^2 + C(2)∗X + C(3)
Coefficient	Std. Error	t-statistic	Prob.
C(1)	0.000733	0.000132	5.542924	0
C(2)	5.753184	0.430664	13.35888	0
C(3)	914.8968	175.7349	5.206118	0
R-squared	0.960057	Mean dependent var		4063.855
Adjusted R-squared	0.959059	S.D. dependent var		4921.867
S.E. of regression	995.8865	Akaike info criterion		16.68062
Sum squared resid	79343192	Schwarz criterion		16.76805
Log likelihood	-689.2457	Hannan-Quinn criter.		16.71574
F-statistic	961.4377	Durbin-Watson stat		1.765773
Prob (F-statistic)	0