System identification deals with the problems of building mathematical models of the systems based on observed input/output data from the systems.
In this framework, identification deals with the relationship between the assumptions of an econometric model and the possibility of answering or not, an empirical question using that model.
The card, provided through a program called IDNYC, was supposed to give undocumented immigrants a method of proving their identification when dealing with city agencies, including the schools system and the Police Department, neither of which is allowed to ask about immigration status.
With respect to technical improvements, apart from robust software-engineering, we think it is also necessary to ensure appropriate patient identification (when dealing with thousands of participants) through advanced pattern matching methods which may rely on a combination of patient demographics and risk factors.
This paper explores the identification problem when dealing with physiological models relating to anaesthetic drugs such as fentanyl.
This is crucial for confident protein identification, especially when dealing with large molecules, such as the ones usually obtained from transmembrane protein digests.
Importantly, the applied MDR approach was developed as nonparametric and genetic model-free data mining strategy for epistasis identification in studies dealing with relatively small sample size [ 28, 57].
This validation step is extremely important for avoiding the overfitting problem associated with statistical analysis in biomarker or classifier identification, especially when dealing with a small cohort (e.g., <40).
It is therefore not too surprising to find that different peak callers can generate quite different results in terms of binding site identification, particularly when dealing with peaks with weak signals [ 23, 31].
In this paper, we propose a least-squares-based non-recursive identification algorithm capable of dealing with slowly time-varying parameters.
