More flexibility, better approximation of the fracture locus and more convenient shape of the fracture envelope might be reached when the strain hardening exponent is considered as another independent parameter of the fracture criteria in the identification process.
Our approach is to exploit the flexibility of wavelet approximations to approximate the unknown response curve by its wavelet expansion thereby eliminating the mathematical difficulty associated with the unknown structure.
Theorem 2 and its corollary give great flexibility for PER approximations in block fading channels.
The advantages of neural network models are summarized: universal approximation capabilities, flexibility, and parsimony.
In particular, the minimum information pair-copula model shows greater flexibility and produces better approximation of the joint probability density and corresponding measures have capability for effective hazard assessments.
The progressive-iterative approximation brings more flexibility for shape controlling in data fitting.
The recently proposed EASI demand system (Lewbel and Pendakur [2009]; for application see e.g., Stasi et al. [2011]) would have been an alternative due to its flexibility with respect to the approximation of Engel curves.
To test this hypothesis, we have investigated how structural disorder, as an approximation for conformational flexibility, changes among Dengue viruses and other flaviviruses, e.g., yellow fever virus, Japanese encephalitis virus, and West Nile virus.
A little used implication of the Michaelian competitive inhibition model is that the parameters k i are equal to the Km of each chemical (Luecke and Wosilait 1979), but that is still an approximation, without the flexibility to go beyond simple competition or the simplicity of our model building approach.
In particular, the EM-algorithm applied to this marginal likelihood is computationally slow, a marginal likelihood gives biased ML estimates for variances, and the regression approximation confers additional flexibility for modeling different distributions for the phenotype as well as different mean-variance relationships.
