From the simulation results, we find that the location estimation error will decrease with the increase of the Q value.
Variable step size is controlled by the instantaneous square error of each iteration, i.e., lower error will decrease the step size and vice versa.
As shown in Figure 4, the probability of error will decrease along with the increase in the number of nodes in the cluster.
Three different second-phase sample sizes were considered because it can be expected that the precision of estimate of the population mean will increase as the sample size increases, that is, its standard error will decrease.
The RSS-MUSIC algorithm has larger estimation error when the angle difference is less than array beam width (16.4°), whereas when the angle difference is greater than array beam width, its estimation error will decrease with the increase of the angle difference.
When testing for difference by timing of CIMT intervention, the margin of error will be no larger than 0.33 standardisation units; as in aim 2, the margin of error will decrease as the correlation between baseline and study-end-standardised units increases.
The emission probabilities are a function of the error rates of the actual sequence data, and increasing error rates will decrease the probability of observing IBS* sequences for both IBD = 2 and IBD ≠ 2 states.
Given this, we ran the Random Forest algorithm two more times; i) on the species pairs from Cliff, Indian, and Webster lakes, to test whether the classification error rate will decrease when considering these three lakes only and ii) on the species pairs from East and Témiscouata to test whether genetic parallelism specific to these two species pairs is present.
Given the same frequency increment errors, the variances will decrease when the number of elements is increased.
The proportional-integral design will avoid the steady-state error, but it will decrease the responsiveness by almost 1° of magnitude.
