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The spatial and temporal convergence is documented and is in agreement with the nominal order of accuracy of the solver.
As apparent from the table, the nominal order of convergence of the new ADER-Prim scheme is recovered with very good accuracy.
The computed order should be equal to the nominal order of each scheme as long as the solution is smooth, gradually degrading to first order as the caustic is approached.
This restriction arises from the need to ensure that the viscosity converges to zero fast enough not to spoil the overall convergence of the scheme at the nominal order.
Partial eta-squared values for the three methods are summarized in Table 2. Here, for sex, RT, and difficulty, the nominal order of the amount of experimentally relevant variance in the statistical effects was the same, largest in the PCA-Gabor, next in the PCA, and the least in the SMP-Gabor.
While all the schemes converge to the nominal order, it is interesting to note that the smallest (L_{2}) error is obtained for the new ADER finite volume scheme in primitive variables, and that the difference with respect to the other two reconstructions increases with the order of the method.
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It works for any number of annotators, is applicable to different variable types and metrics (e.g., nominal, ordered, interval,...), and can handle small sample sizes.
The scheme becomes specifically attractive when the various estimators are adaptive identifiers for the plant which is being modeled as possessing different possible amounts of unmodeled dynamics including different nominal orders and parametrical uncertainties.
Ringleb's flow problem is used to demonstrate that nearly nominal orders of accuracy for schemes up to fourth-order can be achieved in smooth regions using the new limiter.
The relationship between the nominal Orders Corallimorpharia and Scleractinia is controversial the former is either the closest outgroup to the Scleractinia or alternatively is derived from corals via skeleton loss.
The method is well suited in situations where we know a stabilizing controller of a nominal reduced order model, which we would like to robustify with respect to high order dynamics.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com