Information contained in design points of experiments with correlated observations

summary:A random process (field) with given parametrized mean and covariance function is observed at a finite number of chosen design points. The information about its parameters is measured via the Fisher information matrix (for normally distributed observations) or using information functionals depending on that matrix. Conditions are stated, under which the contribution of one design point to this information is zero. Explicit expressions are obtained for the amount of information coming from a selected subset of a given design. Relations to some algorithms for optimum design of experiments in case of correlated observations are indicated

Design for regression models with correlated errors

Abstract The present article is a draft of a chapter in the Handbook of Design and Analysis of Experiments and provides a survey of results on experimental design for linear regression models with correlated responses.

Design for regression models with correlated errors

The present article is a draft of a chapter in the Handbook of Design and Analysis of Experiments and provides a survey of results on experimental design for linear regression models with correlated responses