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Finally we show how state-dependent, Poisson sampling alters the temporal dependence.
Subsequent analyses examined whether cases of dependent evolution consisted of mutual or temporal dependence (Additional file 1: Table S8).
Finally we show how nonlinear, state-dependent, Poisson sampling alters the unconditional distribution as well as the temporal dependence.
Nonlinearities in the drift and diffusion coefficients influence temporal dependence in diffusion models.
Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models.
Nevertheless, ignoring the temporal dependence in small samples may not lead to accurate inference.
We study this link using two notions of temporal dependence: beta-mixing and rho-mixing.
However, they do not possess a universal, straightforward temporal dependence.
If there is a coordinate system for which none of the metric coefficients contain any temporal dependence, then the metric is called "Stationary 4.
We study this link using three measures of temporal dependence: rho-mixing, beta-mixing and alpha-mixing.
Clearly, the temporal dependence of the de Sitter metric is far more extreme as compared to the Einstein de Sitter metric or many other FRW solutions.
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