Estimation of model quality

This paper gives an introduction to recent work on the problem of quantifying errors in the estimation of models for dynamic systems. This is a very large eld. We therefore concentrate on approaches that have been motivated by the need for reliable models for control system design. This will involve a discussion of eeorts which go under the titles of`Estimation in H 1 ', `Worst Case Estimation', `Estimation in`1 ', `Information Based Complexity', and`Stochastic Embedding of Undermodelling'. A central theme of this survey is to examine these new methods with reference to the classic bias/variance tradeoo in model structure selection.