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The ARIMA (p, d, q) models are first introduced by Box and Jenkins in 1970 [42] for purposes of modeling time series data.
The kinematic and dynamic models are first presented.
In this review, the varying triple-frequency AR models are first compared.
The theoretical assumptions at the basis of these models are first reviewed.
In this regard, various corotational stress rate hypoelasticity models are first studied.
Linear models are first derived from the original nonlinear model on several operating points.
Similar(8)
Most of these discrete mathematical models are first-order functional difference equations.
Chosen models are: first-order Markov approach[7], semi-Markov approach[10], and dynamic Markov approach[9].
Fitted models are first-order polynomials for all time periods, corroborating earlier results [17], [28].
Monophone models were first created using all 19,688 sentences.
Univariate regression models were first used to replicate previously described associations.
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