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In statistical analysis the usefulness of confidence intervals is undeniable. Taking into account the uncertainty associated with samples, the estimation of the population parameters can be performed by confidence intervals. In other words, as long as there is randomness and finite sample size (which define the reality) estimation of statistical indicators will be done by confidence intervals. Inspired...
In this paper we perform a local sensitivity analysis with respect to parameters and initial conditions for a SEIT (susceptible, exposed in the latent period, infectious, and treated/recovery) epidemic model. Applying QR decomposition with column pivoting to the relative sensitivity matrix, we evaluate the relative identifiability and sensitivity of the parameters in the inverse problem, and order...
The k-nearest neighbor algorithm is one of the most suitable method of classification for its simplicity, adaptability and performance. The real problem arises when classes do overlap and when samples size is unevenly distributed between categories. Many studies present optimization techniques on discriminant metrics, on weighting the features, on using probabilistic measures or adjusting the prototypes...
We present the numerical simulations of a system composed by three nonlinear partial differential equations modeling the subcutaneous injection of insulin analogues. The equations describe the interaction and dissociation of insulin analogues in the hexameric form into smaller entities, dimers and monomers. The numerical results of the full system are compared with those of the reduced order system...
In this paper we study a prey–predator model defined by an initial–boundary value problem whose dynamics is described by a Holling type III functional response. We establish global existence and uniqueness of the strong solution. We prove that if the initial data are positive and satisfy a certain regularity condition, the solution of the problem is positive and bounded on the domain Q=(0,T)×Ω and...
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