Collecting spatial data: Optimum design of experiments for random fields

Collecting Spatial Data: Optimum Design of Experiments for Random Fields

Volumn , Issue , 2007, Pages 1-242

  Müller, Werner G ^a  

^a JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84892205078     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-540-31175-1     Document Type: Book

References (24)

1. Aptech, Inc., (1993). GAUSS-386 Command Reference. Washington.
2. Dhrymes, P. J. (1984). Mathematics for Econometrics. Springer Verlag, New York.
3. Fedorov, V. V. (1974). Regression problems with controllable variables subject to error. Biometrika, 61:49-56.
4. Fedorov, V. V. and Müller, W. G. (1989). Comparison of two approaches in the optimal design of an observation network. Statistics, 20 3:339-351.
5. Fedorov, V. V. and Müller, W. G. (1997). A reparametrization view of optimal design for the extremal point in polynomial regression. Metrika, 46:147-157.
6. Fedorov, V. V. and Müller, W. G. (2007). Optimum design for correlated fields via covariance kernel expansions In mODa8, Lápez-Fidalgo, J., Rodriguez-Diaz, J., and Torsney, B., editors. Physica Verlag, Heidelberg.
7. Golub, G. and Van Loan, C. (1983). Matrix computations. Johns Hopkins University Press, USA.
8. Hill, P. D. H. (1980). D-optimal design for partially nonlinear models. Technometrics, 16:425-434.
9. Kubácek, L., Kubáckova, L. and Volaufová, J. (1995). Statistical Models with Linear Structures. Veda Publishing House.
10. Müller, W. G. (1991). On Moving Local Regression. Unpublished doctoral thesis at the University of Vienna.
11. Müller, W. G. (1999). Least squares fitting from the variogram cloud. Statistics & Probability Letters, 43:93-98.
12. Müller, W. G. (2000). Coffee-house designs. In Atkinson, A. C., Bogacka, B., and Zhigljavsky, A. A., editors, Optimum Design 2000, forthcoming. Kluwer.
13. Müller, W. G. and Pázman, A. (1995). Design measures and extended information matrices. Technical Report 47, University of Economics, Department of Statistics, Vienna.
14. Müller, W. G. and Pázman, A. (1996). Design measures and extended information matrices for optimal designs when the observations are correlated II. Technical Report 48, University of Economics, Department of Statistics, Vienna.
15. Müller, W. G. and Pázman, A. (1998). Design measures and approximate information matrices for experiments without replications. Journal of Statistical Planning and Inference, 71:349-362.
16. Müller, W. G. and Pázman, A. (2003). Measures for designs in experiments with correlated errors. Biometrika, 90(2):423-434.
17. Müller, W. G. and Zimmerman, D. L. (1995). An algorithm for sampling optimization for semivariogram estimation. In Kitsos, C. P. and Müller, W. G., editors, Model-Oriented Data Analysis 4, Heidelberg. Physica, 173-178.
18. Müller, W. G. and Zimmerman, D. L. (1997). Optimal design for semivariogram estimation. Technical report #51, University of Economics, Department of Statistics, Vienna.
19. Pázman, A. (1993). Nonlinear Statistical Models. Mathematics and Its Applications. Kluwer Academic Publishers, Dordrecht.
20. Pázman, A. and Müller, W. G. (1998). A new interpretation of design measures. In Model-Oriented Data Analysis 5, Atkinson, A. C., Pronzato, L., and Wynn, H. P., editors. Physica-Verlag, Heidelberg.
21. Pázman, A. and Müller, W. G. (2001). Optimal Design of Experiments Subject to Correlated Errors, Statistics & Probability Letters, 52:29-34.
22. Pukelsheim, F. (1993). Optimal Design of Experiments. John Wiley & Sons, Inc., New York.
23. Rao, C. R. (1973). Linear Statistical Inference and Its Applications. Wiley, New York, 2nd edition.
24. Ripley, B. D. (1981). Spatial Statistics. Wiley, New York.