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So the S αS distribution can not describe the practical noise perfectly as it is colored.
The bottom panels show the fraction F of realizations (out of 100) for which the exponential distribution can not be rejected.
Bold font marks cases where the value of the Anderson-Darling statistic A 2 is smaller than the critical level A 0.05 2 = 2.492 (large-sample approximation) and the hypothesis of two datasets being sampled from the same distribution can not be rejected at a 5% significance level.
This distribution can not be observed for the other values of k.
In contrast, for a mechanism where MT production is independent of existing MTs (random nucleation) and where no other non-linear dynamic effects are included, the MT distribution can not exceed the steepness of the RanGTP gradient (Figure 3A, right panels, 3B (dashed line), and 3C (dashed line)).
A correct distance distribution can not be represented by the formulations used in [29,31] when applied to complex geometries.
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While the distributional approach of this paper is timely and expands the range of model behaviors, it remains a continuous, deterministic treatment and the stochastic implication of rare events stemming from the tails of distributions can not be understood.
Unfortunately the parameters that characterize our original pairwise alignment distribution ν can not vary from branch to branch without inducing unequal length distributions.
As we have seen in the previous examples, a normal distribution can typically not be expected for general, nonlinear ODE models, even if the initial distribution is assumed to be normal.
This paper considers structural reliability assessment when statistical parameters of distribution functions can not be determined precisely due to epistemic uncertainty.
The nucleosome distribution difference can not be completely explained by GC content difference between exon and intron [ 13].
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