Asymptotic inference from sequential design in a nonlinear situation

Abstract

It is shown that confidence regions for nonlinear parameters constructed by the repeated-sampling principle, are asymptotically valid for sequential designs in general linear models. The related questions of consistency of parameter estimators and convergence of sequential design to an optimal design are answered positively. An empirical finding of Ford & Silvey (1980) is given a theoretical justification.