Exact(1)
Second-order Monte Carlo simulation captures parameter uncertainty – distributions are specified on all transition probabilities and utilisation variables and a different value from each distribution is chosen during each simulation.
Similar(59)
In related research contributions, intervals have been proposed as a means to capture parameter uncertainties.
To capture parameter uncertainty, input variables in our model are probabilistic values.
To capture parameter uncertainty, input variables were modelled as probabilistic values.
The variation in effects, in terms of both reduced fracture risk and utilities, as well as direct health care costs, was included in the probabilistic sensitivity analysis, which was done using statistical distributions to capture parameter uncertainty.
Another alternative, used by one of the authors, is to note than many elements of the computer code required for an analysis are common to most models – capturing parameter estimates, −2×log-likelihood, the eigenvalues, calculating the goodness-of-fit – and having written code for these a variety of models can be investigated with minimal additional effort.
Figure 3 Clean data capturing parameters.
In our proposal, a software agent is embedded in each camera and controls the capture parameters.
This figure shows the interface of the system, where the user can configure the capture parameters through the interface before the capture starts.
We have studied the effect of variation in the CO2 capture parameters as suggested previously in the literature (Abu-Zahra et al. 2007; Singh and Rao 2014a, b).
Bayesian optimal design provides an effective alternative to capture parameters uncertainty, which has been widely employed in SSADT design by optimizing specified utility objective.
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