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Moreover, via the use of a cogent finite element model, this criterion is also shown to be applicable for the design of micro-porous materials.
However, it is shown in [1] that even when the vocal tract filter follows an actual all-pole model, this criterion of goodness is not fulfilled by the classical minimum variance predictor.
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Because these are phenomenological models, this criterion does not necessarily mean that the non-linear model more accurately portrays the biology of the system or that it is better for the purposes of predicting response to climate change.
While considering the difference induced by only two models, this criterion is amenable to efficient computation via an integer linear programming formulation, allowing us to learn a de novo experiment that maximizes this criterion over all optimal models, eliminating the need to enumerate models or to suggest candidate experiments a priori as in the maximum entropy approach.
When covariates were included in the latent class regression model, the 3 class model also had the minimal Chi-square goodness of fit value (χ = 274.80), indicating the preferred model on this criterion [ 27].
Values of CMIN/DF lower than 2 indicate an acceptable fit [ 32- 34], and our model fulfilled this criterion (CMIN/DF = 1.117).
Having the disease under control as an outcome of care was not introduced into the model, since this criterion was considered not to be relevant in the study context.
For the inference model(2), this criterion can be defined as χ 2 = 1 N n − P ∑ i = 1 n ∑ k = 1 N 1 ψ i k 2 [ y ^ i (t k + 1 ) − y ^ i (t k ) (1 + w i i Δ t k ) − ∑ j = 1 j ≠ k n w i j y ^ j (t k ) Δ t k − b i Δ t k ] 2 where y ^ i (t k ) are the measured time series, ψ ik are the statistical weights and P is the number of estimated parameters.
The models were considered acceptable if p > 0.05 and all models met this criteria.
The Akaike's information criterion (AIC) of each model is defined as 2 k - 2· lnL, and the lowest value, corresponding to the best model according to this criterion is in bold font.
Secondly, based on this model, the criteria for the asymptotical stability analysis and control synthesis of event-triggered networked control systems are established in terms of linear matrix inequalities (LMIs).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com