Beyond space-filling: An illustrative case

When collecting spatial data, it has become a standard practice to position the measurement points spread out uniformly across the available space. These so-called space-filling designs are now ubiquitous in corresponding publications and conferences. The statistical folklore is that such designs have superior properties when it comes to prediction and estimation of response functions. In this presentation we want to review the circumstances under which this superiority holds, provide some new arguments and clarify the motives to go beyond space-filling. We will accompany these findings with a simple two-dimensional example with seven observations.

[1]  Oleg A. Smirnov Computation of the Information Matrix for Models With Spatial Interaction on a Lattice , 2005 .

[2]  Luc Pronzato,et al.  Design of computer experiments: space filling and beyond , 2011, Statistics and Computing.

[3]  Daniel R. Jeske,et al.  Mean Squared Error of Estimation or Prediction under a General Linear Model , 1992 .

[4]  Luc Pronzato,et al.  Optimal experimental design and some related control problems , 2008, Autom..

[5]  J. W. van Groenigen,et al.  The influence of variogram parameters on optimal sampling schemes for mapping by kriging , 2000 .

[6]  V. Roshan Joseph,et al.  Limit Kriging , 2006, Technometrics.

[7]  Luc Pronzato,et al.  Relations Between Designs for Prediction and Estimation in Random Fields: An Illustrative Case , 2012 .

[8]  Dale L. Zimmerman,et al.  Optimal network design for spatial prediction, covariance parameter estimation, and empirical prediction , 2006 .

[9]  J. Kiefer,et al.  The Equivalence of Two Extremum Problems , 1960, Canadian Journal of Mathematics.

[10]  M. E. Johnson,et al.  Minimax and maximin distance designs , 1990 .

[11]  Milan Stehlík,et al.  Compound optimal spatial designs , 2009 .

[12]  Markus Abt Estimating the Prediction Mean Squared Error in Gaussian Stochastic Processes with Exponential Correlation Structure , 1999 .

[13]  Zhiliang Ying,et al.  Asymptotic properties of a maximum likelihood estimator with data from a Gaussian process , 1991 .

[14]  M. Stein,et al.  Spatial sampling design for prediction with estimated parameters , 2006 .