In this paper we show how, based on the conjugate gradient method, to compute the covariance matrix of parameter estimates and confidence intervals for constrained parameter estimation problems as well as their derivatives.

The paper is devoted to the study of the cone ${\mathcal{C}OP}^p$ of copositive matrices. Based on the concept of immobile indices known from semi-infinite optimization, we define zero and minimal zero vectors of a subset of the cone ${\mathcal{C}OP}^p$ and use them to obtain different representations of the faces of ${\mathcal{C}OP}^p$ and the corresponding dual cones. The minimal face of ${\mathcal{C}OP}^p$ containing a given convex subset of this cone is described, and some propositions are proved that allow obtaining equivalent descriptions of the feasible sets of copositive problems.