In order to generate the highlights time curve H M (t) [10], the functions G i (t) are filtered using a weighting function, w ( t ) = 1 2 1 + erf G ̄ M ( t ) − d σ (15).
In all Monte Carlo simulations, a data set of 100 noise-added TACs was analyzed with weighted NLS, using a relative weight w i : w i = constant × Δ t i × exp - λ t i C i. (3).
To handle the high-class imbalance in our data, we used a weight-parameter W pos to increase the weight of the positive examples in the logistic loss terms of our function.
It uses a weighting coefficient for VM termination w t ∈[0,1], similar to w p in (3).
Then these two signals are weighted using a Gaussian weighting function, w = [w1w2... w N ] with a standard deviation of 1.5 samples, where Σ i =1w i = 1.
At any particular level of interest, a value or utility function, V, is applied to the aggregate alternative scores, a, and is adjusted using the weight, w, given by the stakeholder for that criterion, m.
In order to avoid such a problem the entropy of each region can be adjusted by using the weight w r = | log 2 max m r, s − min m r, s / MAX − MIN + ϵ | where max(mr,s) and min(mr,s) are the maximum and minimum methylation levels across s samples of region r, respectively, and MAX and MIN the bounds of their possible values (1 and 0, typically).
Sample size was weighted using the relevant weight (w = v005) as recommended by MeasureDHS.
Following the similar procedure for deriving the steady-state MSE of TDes, the optimal solution of TRTap can be acquired in terms of calculating steady-state MSE using the optimal weight w ̂ o as (21).
