Sentence examples for model weighting with from inspiring English sources
When population density was low, the high degree of variation in model weighting with changes to ĉ made determining the combined effects of these two covariates on first-year survival suspect (i.e., the variance among survival estimates was 175 %) [see Additional file 1, table 3].
The advantage of HDLA is that there exist nonnegativity restrictions on the model weights together with (ell _1 -sparsity enforced over the activations of the hidden layer nodes of the network.
Cumulative weights evaluate the strength of evidence for each variable and are a sum of the model weights associated with each model in which the variable appears.
To allow for this uncertainty, we used a weighted linear regression with model weights given by the number of human SAR estimates.
From the five models identified (Table 1), the summed model weights for each factor with respect to crop-raiding were habitat type (100%), elevation (97%) and distance to nearest village (29%).
This result remains robust inalternative models with weighting by country size, clustering, and fixed effects.
Where appropriate, hazard ratios were pooled in meta-analyses using random effects models, with weighting of studies according to the DerSimonian-Laird method.
However, the situation in building weighting model with multiple factors and their correlation are complicated and difficult.
The examples from Germany confirmed that in presence of heteroscedasticity in the model residuals, a weighting with the inverse to the presumed residual variance can be effective [62, ch. 2.11, 63, ch. 2.1].
The examples from Germany confirmed that in presence of heteroscedasticity in the model residuals, a weighting with the inverse to the presumed residual variance can be effective [ 62, ch. 2.11, 63, ch. 2.1].
This analysis is easily performed using linear mixed model software with weighting facility by defining the inverse of var e) as weight and fixing the residual variance at unity [ 13].
