Table 5.

Statistical indicators for verifying the external predictability of proposed MEP models.

S.No.	Mathematical Expression	Requirement	$f_c^{\text{'}}$	$f_{STS}$	$f_{FS}$	Reference
1.	$R=\frac{{{\displaystyle \sum }}_{i=1}^n\left(M_i-{\overline{M}}_i\right)(P_i-{\overline{P}}_i)}{\sqrt{{{\displaystyle \sum }}_{i=1}^n{(M_i-{\overline{M}}_i)}^2{{\displaystyle \sum }}_{i=1}^n{(P_i-{\overline{P}}_i)}^2}}$	R > 0.8	0.92	0.92	0.91	[78]
2.	$k=\frac{{{\displaystyle \sum }}_{i=1}^n(M_i-P_i)}{M_i{}^2}$	0.85 < k < 1.15	1.00	0.99	1.01	[79]
3.	$k^{\prime }=\frac{{{\displaystyle \sum }}_{i=1}^n(M_i-P_i)}{P_i{}^2}$	0.85 < k’ < 1.15	0.98	0.98	1.05	[79]
4.	$R_m=R^2\times (1-\sqrt{\left|R^2-R_0{}^2\right|}$	Rm > 0.5	0.67	0.71	0.64	[80]
	$R_0{}^2=\frac{{{\displaystyle \sum }}_{i=1}^n{\left(P_i-M_i{}^0\right)}^2}{{{\displaystyle \sum }}_{i=1}^n{(P_i-\overline{P_i{}^0})}^2}, M_i{}^0=k\times P_i$	$R_0{}^2\cong 1$	0.98	0.98	0.97
	$\acute{R_0{}^2}=\frac{{{\displaystyle \sum }}_{i=1}^n{\left(M_i-P_i{}^0\right)}^2}{{{\displaystyle \sum }}_{i=1}^n{(M_i-\overline{M_i{}^0})}^2}, P_i{}^0=k^{\prime }\times M_i$	$\acute{R_0{}^2}\cong 1$	0.98	0.99	0.98