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By comparing MSE and MAE, we draw conclusion that the mixed model has better forecasting results in most cases.
From the forecasting results of weekly prices, the mixed model has better forecasting results of price changes.
The mixed model has huge errors because sudden changes of a single market has no direct relationship with price changes of other markets.
The determination of the shoot biomass values (cf. Table S6) via mixed model has been described elsewhere [17].
A mixed model has been used for the statistical analysis: P < 0.05 was considered significant.
Estimation of genetic variance and G × E variance in a linear mixed model has been implemented in the software GCTA (http://www.complextraitgenomics.com/software/gcta/) (Yang et al. 2011).
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There seems to be little difference whether BH or the mixed model approach is used to estimate FDR for limma and Cyber-T on our data set, but since the BH FDR produce values that tend to increase stepwise whereas the mixed model have a more smooth increase (more obvious if Figure 3C is plotted in higher resolution, not shown) we chose to use the mixed model FDR in the following.
Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors.
According to the bivariate linear mixed model, having a diagnosis of dementia and lower score on MMSE were associated with less improvement of the MADRS score.
In the follow-up simulation studies, we have shown that our meta-analysis multivariate nonlinear mixed model had little relative bias (<1%) in estimating compartment model PK parameters if all non-compartment PK parameters were reported in every study.
In simulation studies, we showed that this multivariate nonlinear mixed model had little relative bias (<1%) in estimating compartment model PK parameters if all non-compartment PK parameters were reported in every study.
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