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By using the generalised Dirichlet integral inequality with continuous functions on the boundary of the upper half-space, we prove new types of solutions for the Neumann problem with fast-growing continuous data on the boundary.
We assessed subgroup homogeneity by using the generalised score statistic.
Correlations within general practices (GP) were accounted for by using the generalised estimation equation method (Zeger et al, 1988).
We then transformed category-specific risk estimates into estimates of the RR associated with every 5 kg/m increase in body mass index (BMI) by using the generalised least-squares method for trend estimation.
To examine changes in the likelihood of fatigue, depressive symptoms, and chronic disease, we applied a repeated measures logistic regression analysis by using the generalised estimating equations method with autoregressive correlation structure, as in our earlier papers.
Category-specific risk estimates were further transformed into estimates of the RR in terms of per increase of 5 in BMI by using the generalised least-squares method for trend estimation.
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We did multilevel analysis on each outcome by using the iterative generalised least squares method of estimation.
The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion.
The features extracted using the generalised and region-by-region approach will be used to evaluate the capabilities of several classifiers considered in this study.
Model performance was evaluated by considering uncertainties in model inputs using the Generalised Likelihood Uncertainty Estimation (GLUE) procedure.
Our analysis used a fixed effects meta-analysis using the generalised inverse variance method.
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