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Thus the additional moments can be reconstructed using the variables and their first moments, resulting in a very substantial savings in computer memory.
The GRBFNN according to the architecture depicted in Fig. 2 was trained using the variables and data sets as the statistical ARIMA(1,1,0)/EGARCH(1,1) model above.
Using the variables and their respective weightings identified in the derivation cohort (table 2), individual risk of AHFS was predicted.
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We also estimated the relative contribution to global risk by each individual measure of kidney function using the variable and model likelihood ratio χ statistic.
Third, the study was confined to using the variables collected and stored in the prospective database.
eIn contrast to Jürges [1], we refrain from using the variables walking speed and grip strength.
ANOVA was then performed using the variables sex, specialty, and years since training.
Using the variable selection and model building wizard, the model was built by stepwise-forward method [ 42].
Control simulations using the variable sampling period and fixed sampling period are compared.
We perform model calculations for the GCR intensity using the variable solar wind and the corresponding magnetic field.
For the analysis in this study, we used the variables listed and defined in Table 1.
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