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Exact(8)
We model this dependence structure by applying a binary variable (0 = reject the null hypothesis; 1 = accept the null hypothesis).
If in the spirit of the hard sphere model this dependence is parameterized in terms of η, then a satisfactory fit may be obtained.
Generalized Estimating Equation (GEE) methods, using a compound symmetric working correlation structure, were used to model this dependence.
We model this dependence by setting the rate of probability for a mutation to occur, (1) r M = α D 2 D 2 + 1.
We model this dependence by assuming that evolution at the third codon position occurs according to our full context-dependent GTR16C model [ 13].
This demonstrates that the simulated value of s has some effect on the expected patterns of diversity (which is not predicted by the results of Wiehe and Stephan 1993, which we used to build Algorithm 1) and that (9) does not appropriately model this dependence.
Similar(52)
For the ABA triblock copolymer, slight dependence of the partition coefficient on B block length was observed even for the RW model while this dependence became much stronger when the chain was modeled by SAW model.
Our model reproduced this dependence on indicator concentration.
On this model, the dependence of the amount of Ca released from the SR on free SR Ca concentration (Ca) is given by: Ca release = r × Ca × C a n C a n + K d n The fraction of SR Ca that is released is therefore equal to r × [ C a n / (C a n + K d n ) ], where r is independent of SR Ca. In other words, the fractional release increases with SR Ca with a steepness determined by n.
Using step-functions to model this time-dependence, it was already shown by [ 10] that d has a linear impact on the overall survival after recurrence.
An autoregressive model may therefore be more appropriate for the quantification of the impact of WNV than a model that ignores this dependence.
Related(20)
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Justyna Jupowicz-Kozak
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