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In order to design an observer for a dynamical system it is usually required that the model of the process is observable, or at least detectable.
According to this view, it is required that the model can be described as a computer program, and that the program can be run in a feasible time.
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A clinically relevant spinal cord regeneration animal model requires that the model mimics specific pathologic processes that occur in human SCI.
This is an example of a classical ill-posed problem; it is regularized by requiring that the model be near to a given one.
Note that this requires that the model of the probability of detection be correct, otherwise, the risk of degeneracy increases in a particle filter with a limited number of particles.
Different from our previous work (Fluid Phase Equilibria, 206, 41 59, 2003), the criteria developed here do not require that the model parameters depend on moments of a characteristic property (e.g. molecular weight) used to characterize the distribution of components.
Software design was based on an anticipated cycle of adaptive hypothesis testing, requiring that the model implementation be highly modular, quickly extensible, and easily coupled with hydrologic models in a shared state space.
Partial MI requires that the model parameters of interest (i.e. the factor loadings and/or the thresholds) of at least two items remain invariant across all groups; the invariant items then define the meaning of these latent variables (Byrne et al. 1989; Steenkamp and Baumgartner 1998).
Gene models were then filtered by requiring that the model translation find the original D. melanogaster query translation among the top hits in a reciprocal BLASTP search against the D. melanogaster translation set (e-value threshold 1e-10).
This, or any, model of assigning reads to bins requires that the model is reasonable.
This can only be done by first requiring that the model be "causally consistent" (see below).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com