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Normality tests of residual errors were performed using the Shapiro-Wilk test in SPSS.
The variance of residual error signal can be adopted as residual error evaluation function.
Residual error series were obtained, respectively, via residual error generator designed using CPRBF network, and each variance of residual error series was calculated correspondingly.
Human error in the modeling process is accessed in terms of residual error.
Across a population of 10 VPs, the average [Gbl] under MPC is 6.31 mmol/l, the average minimum is 4.62 mmol/l, the population individual minimum is 3.49 mmol/l and the average absolute average residual error is 0.83 mmol/l from a 5.6 mmol/l target.
According to exterior checking of the 44 continuous GPS stations in the study area, the averages of the residual errors (RMSexterior) obtained using the Kriging method for the north and east components are ±1.9 and ±2.2 mm/year, respectively, and those obtained using the block model are ±2.0 and ±2.9 mm/year, respectively.
At different order of approximations (m), minimum of average residual errors are shown in Tables 1, 2 and 3.
The constant α is a ratio by which the squared difference between the estimated and measured blood concentrations has more influence on the fitting process than the average of the squared residual errors of the modelled m tot(t) values.
It can be seen from Table 2 that the minimum of average residual error for (theta) attains at (h_2=-0.93 h_2=-0.93
The average values of the residual errors obtained using the Kriging method for the north and east components are ±1.9 and ±2.2 mm/year, respectively, whereas those obtained using the block model are ±2.0 and ±2.9 mm/year, respectively.
While it is also seen that in Figure 1(a), where for viscoelastic parameter (K=0.1) it is observed that as the order of approximation is increased the total averaged squared residual errors and averaged squared residual errors are getting smaller, but when (K=0.2), the error is increased as compared to the case for (K=0.1) as shown in Figure 1(b).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com