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Since in this range different water sorption models can fit the experimental data well it is hard to decide which model is the most correct.
Regardless, IRT models can fit well and can still provide us with information about the measurement error.
We demonstrate that several plausible models can fit observations, and we interpret the models which best reproduce the observed short GRB detection rate and redshift distribution.
Even in cases where the test was not constructed explicitly with IRT in mind, IRT models can fit well and provide strong information about measurement error.
There is, therefore, evidence that neutral models can fit empirical data at some scales, but not at others.
We have shown that in some cases, different models can fit equally well particular types of data while in other cases different models lead to different parameter estimates.
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In addition, we also demonstrate that the model can fit to the experimental data.
All the Freundlich, Langmuir and Dual-mode model can fit the sorption data of each BC well.
The analytical results showed that the prediction accuracy of the models was approximately 90%, indicating that the exponential smoothing model can fit the variation of heavy metal pollution.
The author of this piece, Marco Thornagel from Sigma Engineering, explains how a mathematical model can fit in with the realities of production….
If the model can fit historical data, in particular relative to the productive decline of specific fisheries, then we have a strong indication that the decline of the fish stock is driving the decline of the fishery production.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com