On the use of general positive quadratic forms in simultaneous inference

Abstract

Some aspects of using general positive definite quadratic forms to project simultaneous confidence intervals for scalar linear functions of a parameter vector are explored. Firstly, a criterion is introduced according to which Scheffe’s S-method (using the inverse of the dispersion matrix of the allied estimators) is optimal. Secondly, it is shown how to construct simultaneous confidence bands (for regression surfaces) with minimal confidence interval length at a given arbitrary point.