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Hence we have the following definition of inverse uncertain distribution.
The uncertain distribution of the maximal travel time is first derived and then a chance constrained programming model is formulated.
The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation.
All the transition intensity matrix, observation plan and counting intensity are parameterized by a random vector with uncertain distribution on a known support set.
For estimating the effect of uncertain distribution parameter on the variance of failure probability function (FPF), the map from distribution parameters to FPF is built and the high efficient approximation form is extended to solve the parametric variance-based sensitivity index.
Because of the unknown and uncertain distribution of the indices, for revealing chromosomal features one cannot do significance tests based on conventional statistical methods.
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It is important to clarify that we were not simulating individual patient experiences but rather repeatedly sampling the differences between treatments in each of the uncertain distributions (i.e., our analysis was at the level of a cohort of patients as reflected in trial results).
We consider two phase flow and transport in heterogeneous porous media with uncertain permeability distribution.
Finally, we present as an application the study of structures with uncertain mass distribution.
This may be a consequence of the uncertain dust distribution or else a real difference in the dust properties in the region which was observed by Zagury et al. (1998).
From information theory, the most uncertain probability distribution is the one that maximizes the entropy term: E = - mathop sum limits_{k} pleft( {A_{k} } right)ln p(A_{k} ) (5).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com