We used two indices: the standard deviation of relative difference (SDRD) and the mean absolute bias error (MABE).
Moreover, with a view to show performance analysis of models, the statistical testing methods such as mean absolute percentage errors (MAPE), mean absolute bias error (MABE), root mean square error (RMSE) were used.
Among the methods for estimating the field mean moisture content using the representative locations, i.e. minimal SDRD (standard deviation of relative differences), ITS (index of temporal stability), MABE (mean absolute bias error), and RMSE (root mean square error), the minimal SDRD with a constant offset provided the best results.
To indicate the performance of the models, the following statistical test methods are used: the coefficient of determination (R2), mean bias error (MBE), mean absolute bias error (MABE), mean percent error (MPE), mean absolute percent error (MAPE), root mean square error (RMSE) and the t-statistic method (tsta).
In order to evaluate the day by day performance of these models, a statistical analysis was performed by using several statistical indicators of mean absolute bias error, root mean square error, normal root mean square error, test statistic, standard deviation and coefficient of determination.
For Bandar Abbass station, the obtained mean absolute bias error (MABE) and correlation coefficient (R) for the ELM model at different depths are in the range of 0.9116 1.5988 °C and 0.9023 0.9840, respectively while for the SaE-ELM model they are in the range of 0.8660 1.5338 °C and 0.9084 0.9893, respectively.
For both men and women and across Panels 4 and 5, we observe low values for the mean and median absolute bias.
The correlation between the predicted calibration coefficients from each city and the observed by-city coefficients was 0.62 (p-value = 0.05), the mean percent relative bias was estimated -0.76% and the mean percent absolute bias 149%.
Inter- and intra-observer reproducibility of ADC and SUV of tumours were determined as mean absolute difference (bias) and as 95%% confidence interval (CI) of the mean difference (limits of agreement), according to the methods of Bland and Altman [ 19].
In general, a lower mean percent absolute bias is a sign that matching was able to reduce differences of observables between treated and control units.
As described previously (Marshall et al. 2008), model measurement comparisons for NO at monitoring station locations indicate reasonable to good agreement (mean bias, absolute bias, and error, 29%, 42%, and 1.6 μg/m, respectively; model measurement correlation, 0.7).
