In this chapter, we propose to use a parametric multiplier approach to deriving parametric Lyapunov functions for robust stability analysis of linear systems involving uncertain parameters. This new approach generalizes the traditional multiplier approach used in the absolute stability literature where the multiplier is independent of the uncertain parameters. Our main result provides a general...

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propos...

in this article the general non-symmetric parametric form of the incremental secant stiffness matrix for nonlinear analysis of solids have been investigated to present a semi analytical sensitivity analysis approach for geometric nonlinear shape optimization. to approach this aim the analytical formulas of secant stiffness matrix are presented. the models were validated and used to perform inve...

This paper presents an approach to mine parametric state-based specifications from execution traces, which can involve multiple components. We first discuss a general framework for mining parametric properties from execution traces, which allows one to apply non-parametric mining algorithms to infer parametric specifications without any modification. Then we propose a novel mining algorithm tha...

We consider a linear algebraic system A(p)x = b(q), where the elements of the matrix and the right-hand side vector are linear functions of uncertain parameters varying within given intervals. The linear tolerance problem for the so-called parametric tolerable solution set Σtol(A(p), b(q), [p], [q]) = {x ∈ Rn | (∀p ∈ [p])(∃q ∈ [q])(A(p)x = b(q))} requires an inner estimation of this solution se...