It is shown that the multivariate uncertainty analysis method fails when the perturbations are relatively large and/or the output distribution is non-Gaussian, and therefore the Monte-Carlo analysis should be used in the general case.
Then, to understand how uncertainty on parameters would affect uncertainty on the results obtained for each strategy described in table 3, we performed multivariate uncertainty and sensitivity analyses including all parameters except those defining each strategy (detection and cure rates).
Multivariate uncertainty and one-way sensitivity analyses were performed.
Then we conducted multivariate uncertainty and sensitivity analysis to determine the uncertainty in the performance measure that was due to the uncertainty in estimating the input parameters.
For all projections, 95% credibility intervals (CrI) were generated from the multivariate uncertainty sampling.
We performed double-trait genome scans using our recently developed multivariate analysis method implemented in the MultiABEL package9.
"Entropy Balancing: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies". Political Analysis.
Kernel Principal Component analysis is a nonlinear generalization of the popular linear multivariate analysis method.
An analytical multivariate method based on a first-order Taylor series expansion and a numerical Monte-Carlo method based on assumed uncertainty distributions for the input variables are considered.
Authors provide critical overview on the good modeling practices and introduce concepts of multiple-unit, adaptive and dynamic design space, multivariate specifications and methods for process uncertainty analysis.
