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What expansion order p to use?
Let the optimal detection order p = [k1, k2,..., k N ].
These results are then applied to the estimation of local discretization errors for methods of order p and for the adjacent order p+1.
The results show exponential error convergence of order p + 1∕2 for smooth solutions.
Such a set includes, e.g., any generalized mean of order p of the agents' initial states.
It should be noted that the moment of order p of the relevant distribution represents the structure functions (SFs) of order p at a given time lag.
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However, in [20, 23], Jankowski only dealt with third order p-Laplacian equations and fourth order p-Laplacian equations.
For this one needs to use a new technique to deal with second order p-Laplacian equations with deviating arguments, especially for second order p-Laplacian equations with impulsive effects.
Our final SARIMA model contained first-order (p = 0.0155) and second-order (p = 0.0167) moving average terms, a first-order seasonal (period of 12) moving average term (p = 0.0169), and an upward linear time trend (p < 0.0001).
Clearly, the (operatorname{SDD}(p)) matrix is a 2nd-order p-norm SDD tensor.
In this paper, we consider the following high-order p-Laplacian generalized neutral differential equation.
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