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7 These frameworks provide input-output "transfer function" models similar to PD modeling but comprise many more variables, as required for a systems perspective.
Experiments reveal that different coefficient distribution may have different best function models for state selection.
We employ the function models with estimated parameters to get these probabilities.
Our proposed method maps coefficients with the Markov states according to various function models.
Each new basis function models a finer resolution detail in the space being spanned.
Transfer function models are used in series related to one or more entry series.
Specifically, the Gaussian Copula function models the dependency among multiple Gaussian distributed variables.
The polynomial function, the composite function, and Fermi function are the common function models [15].
Transfer function models can be used to model single-output and multiple-output systems [16].
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Next, we examined gain-of-function models.
However, this is not evident from REST loss-of-function models.
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