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Checking whether the output of a model transformation is correct is a manual and error-prone task, referred to as the oracle problem.
The study of how the uncertainty in the output of a model can be apportioned to the uncertainty in the model inputs is the job of sensitivity analysis.
Recent work has shown that it is possible to establish asymptotically valid confidence intervals for a quantile of the output of a model simulated using variance reduction techniques (VRTs).
By comparing the reduction in FFR strength when high-pass masking noise was added to the output of a model of the auditory periphery, the results provide evidence for the FFR to low-frequency dyads resulting in part from basal cochlear generators.
As a particular implementation of the proposed framework where continuous arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) are available, we propose to simulate the unobserved ICP as the output of a model built from a database composed of arterial blood pressure, cerebral blood flow velocity and ICP.
In general, the electrical power output of a model wind turbine is commonly rely on cut-in, rated and cut-off wind speeds.
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The figure below shows the group size average output for a model run of each of the three model variations.
The figure below shows the age distribution output for a model run of each of the three model variations.
In this study, a methodology to relate the uncertainty on the output of a PLS model to the uncertainty on the model inputs is proposed.
In this method, the linear combination of the value forecasted by individual models is considered the output of a hybrid model and the desired weight of each component is calculated using different weighting approaches.
The output (pond temperature) for each trial model run was compared to the output of a standard model run.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com