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Representing these functions in a Taylor series enables an analytical solution of the optimal design problem for many nonlinear models.
However, in nonlinear contexts, where one might be constructing a model from a data set generated by observing a system, there are potentially many nonlinear models that can be constructed, where each model is as empirically adequate to the system behavior as any other.
The indirect method fitted many nonlinear models to each time series.
There are many nonlinear models besides the piecewise and sigmoidal functions we considered that might be used to determine the general shape of the attribute-pressure relationship [59].
Many nonlinear models are impossible to solve theoretically and our intuition of how a nonlinear system reacts to perturbations is often wrong 34, because a nonlinear system is not equal to the sum of its parts.
Third, whereas all the parameters of the PSHO model can be estimated using only coarse features of a measured expression level signal - period, amplitude, and offset, - the same may not hold for many nonlinear models because these generally have many more unknown parameters.
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Many nonlinear subspace models have also been proposed, such as self-organizing map (SOM), auto-encoders, auto-associative networks [28], and kernel PCA [29].
The computer programs for Bayesian analysis allow many (nonstandard) nonlinear models to be fit; an example using floor and ceiling effects is discussed here.
There are many nonlinear hybrid impulsive models whose solution cannot be computed analytically as in logistic equation with variable coefficients.
In this context, many nonlinear time series models (see, among others, [1 5]) which have been more effective in capturing certain features of time series data were proposed.
Many different linear or nonlinear models addressing vibrations of continuum appear in the literature.
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