For the computation of uncertainty intervals for our model predictions we propose to follow an approach, based in the method described in Section 2, consisting of three stages: clustering, parameter estimation via maximum likelihood, and probability interval computation.
§6 details the computation of standard uncertainties (s.u.'s), emphasizing the influence of constraints.
The linear computational complexity of the algorithms for computation of the uncertainty bound and implementation of the Norm Optimal ILC law, is achieved through exploiting the sequentially semi-separable structure of the lifted system matrices.
Efficient solutions, with the linear complexity in the size of the trial length, are presented for both the BDU least squares problem and for the computation of the uncertainty bounds in the trial domain.
In this paper, based on a service composition middleware framework, we propose an efficient and reliable service selection approach that attempts to select the best reliable composited service by filtering low-reliability services through the computation of QoS uncertainty.
The purpose of the present study is to introduce an approximate method for the computation of the uncertainty bound of the final epidemic size, which also permits us to discuss simple methods for sample size calculations.
The high-density regions with the uncertainty bands produced the best results as regards to the computation of the total uncertainty.
The computation of the prediction uncertainty accounts for the errors associated to both the estimations of i) SOC stocks and ii) parameters of the spatial model.
We do not address the exact computation of the probabilistic uncertainty of the information before and after the introduction of ITS, which is very much related to the technology and the specific setting, and it is the subject of more technology oriented ITS studies.
This approach allows computation of a measure of uncertainty, the posterior probability of an excess risk (Pr[RR > 1 | data]), associated with the smoothed risk values (Richardson et al. 2004).
