Since the misclassification of exposure is likely to be non-differential related to the outcomes of interest, the level of such misclassification would likely bias the effect estimations toward to the null.
tVIM estimates the effect of 1 variable at a time, which tailors the estimation approach toward the specific effect of interest, thereby providing more accurate effects and assessment of uncertainty.
Figure 2 Examples of eigenvalue estimation bias toward the GSA limit.
The trace shows that even if we have perfect knowledge of y(t) at time slot t, the performance of state estimation degrades toward the crossing point after running a few time slots.
It is not clear how this uncertainty would impact risk estimations, either toward overestimation or underestimation, but it does make such evaluations much more difficult [ 13– 15].
In this study, we propose slip estimation methods targeted toward use in unknown environments.
Carefully designed membership functions and rules preserve the interpretability of FLS as each rule works toward estimation of the specific part of dynamics.
Our proposed approach is part of the process toward estimation of causal effects.
At high SNR, the hemispheric difference curves become shallower, which implies that ITD estimation is biased toward the center.
Figure 9 The estimation of the direction toward which information is propagated.
