Spatial phenomena is commonly modelled as a realization from a stochastic process. Even when the reality is unique such models can usefully represent the uncertainty the modeler has about the phenomena. This paper is concerned with predicting for …
This article is concerned with predicting for Gaussian random fields in a way that appropriately deals with uncertainty in the covariance function. To this end, we analyze the best linear unbiased prediction procedure within a Bayesian framework. …
This paper analyzes data from a study conducted by the United States Office of Naval Research on the effects of pulsed magnetic fields on chick embryos. The experiment involved incubation of eggs under carefully controlled conditions in six different …
In a recent article in the Consultant's Corner section of this journal, Bennett (1988) considers a problem in the area of kinesiology. Apparently, when humans exercise strenuously, an 'anaerobic threshold' is passed; this threshold is defined to be …
This paper is concerned with aspects of the design and analysis of computer experiments. It has been motivated by issues in the experimental design of intergrated-circuits. Suppose we wish to model the behavior of a complex process as a function of …
This is an invited discussion of 'Prediction of Spatial Cumulative Distribution Functions Using Subsampling' by Soumendra N. Lahiri, Mark S. Kaiser, Noel Cressie and Nan-Jung Hsu
This thesis is concerned with aspects of statistical inference for Gaussian random fields when the ultimate objective is prediction. If we wish to predict a value for a random field at unobserved locations in a bounded region it is essential to have …
The impact of using an incorrect covariance function on kriging predictors is investigated. Results of Stein (1988) show that the impact on the kriging predictor from not using the correct covariance function is asymptotically negligible as the …