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We also show how the axial dispersion can be introduced into the RD model, without adopting the axial dispersion model.
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The estimation is derived without adopting conventional performance modeling assumptions, such as Poisson arrivals or exponential holding times, thus allowing non-standard behaviour patterns, including special phenomena of IP networks, such as self-similarity.
The Shannon et al. model was adopted without changes and recent MatLab version of the code has been uploaded (http://somapp.ucdavis.edu/Pharmacology/bers/).edu/Pharmacology/bers/
To model the change in the moving average over time, several functions were considered but, to estimate the model parameters, the adopted model was the one that fitted the best the moving averages without presenting algorithm convergence problems.
Without loss of generality, the exponential correlation model is adopted, where the correlation model at both transmitting and receiving ends of both hops are assumed to be identical.
The Fine-Gray model was adopted for multivariate analysis.
Another model is adopted in Cambridge.
PV model was adopted with identity link.
Otherwise, random effects model is adopted.
Another caveat is that, at this stage, the model adopts a "typical" value for each parameter, without considering intersubject variability.
For simplicity, in the following calculations we adopt a model without lateral gas escape.
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Justyna Jupowicz-Kozak
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