For high dimensional uniform designs we apply the threshold accepting heuristic for finding low discrepancy designs.
One possible explanation for this relatively low discrepancy in older age might be the fact that the prevalence of MetS was more frequent among older persons [ 5, 30].
Numerical experiments show that for lower degree polynomial models and for models with many interactions, low discrepancy designs approximating the arcsine distribution are superior.
Our implementation of this heuristic for the two- and three-level case efficiently generates low discrepancy U-type designs.
The parameters for these reactions are systematically fitted to experimental data using low discrepancy (LD) sequences and response surfaces.
On the other hand, for higher degree polynomial models and those with fewer interactions, low discrepancy designs approximating the uniform distribution are superior.
The systematic review found rather low discrepancy rates.
A low score means a low discrepancy magnitude.
Bases that fail to reach this threshold are called 'N.' The optimum total threshold quality score is determined empirically to be 12, which yields the highest base-call rate with the lowest discrepancy between genotypes for replicate samples.
Although model 2 had the lowest discrepancies for fasts up to 50 days, between 50 and 200 days it was more discrepant than model 3. On average, model 3 provided the least discrepant predictions over the widest duration of fasts.
