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A general variance minimization method is presented to avoid the need for determination of various coefficients and exponents used in regression process.
This concern is relevant because advanced Monte Carlo algorithms, or in general variance reduction techniques, gain their efficiency by exploiting information about the problem, which may require intrusive exchange of information with the system analysis model during the simulation process.
Hence in general variance in SVM and LR differs significantly from NB and RF, whereas between the other methods no real significant differences exist.
In general, variance from these metabolites was poorly explained by PC1 (Additional file 6).
In general, variance component estimates from each dataset and analysis method were very similar.
In general, variance of methylation levels appeared to be markedly higher in saliva as compared to blood DNA.
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Fitting a general variance-covariance matrix however results in important computational difficulties.
Heterogeneity among studies was assessed using the general variance-based method [ 13].
General variance-based methods using CIs were applied to combine the results according to birth weight.
Not all these simplification may be warranted and a more general variance-covariance structure may refine estimates from this model.
The fixed-effects model applied the general variance-based method with inverse variances of individual study effect estimates as weights [ 3].
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