Equidistant and D-optimal designs for parameters of Ornstein-Uhlenbeck process

Statistics and Probability Letters

Volumn 78, Issue 12, 2008, Pages 1388-1396

  Kiseľák, Jozef ^a,b   Stehlík, Milan ^a,b  

^a Physics and Informatics   (Slovakia)

^b JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 49349092013     PISSN: 01677152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.spl.2007.12.012     Document Type: Article

References (21)

1. Abt M., and Welch W.J. Fisher information and maximum-likelihood estimation of covariance parameters in Gaussian stochastic processes. The Canadian Journal of Statistics 26 1 (1998) 127-137
2. Banerjee S., Carlin B., and Gelfand A. Hierarchical Modeling and Analysis for Spatial Data (2004), Chapman & Hall/CRC
3. Cressie N.A.C. Statistics for Spatial Data. 2nd ed (1993), Wiley, New York
4. Dette, H., Kunert, J., Pepelyshev, A., Exact optimal designs for weighted least squares analysis with correlated errors. Statistica Sinica (in press)
5. Fang K.T. Uniform design: Application of number-theoretic methods in experimental design. Probability and Statistics Bulletin 1 (1978) 56-97
6. Goos P., Kobilinsky A., O'Brien T.E., and Vandebroek M. Model-robust and model-sensitive designs. Computational Statistics & Data Analysis 49 (2005) 201-216
7. Hoel P.G. Efficiency problems in polynomial estimation. Annals of Mathematical Statistics 29 (1958) 1134-1145
8. Horst R., and Tuy H. Global Optimization - Deterministic Approaches (1996), Springer Verlag
9. Müller W.G. Collecting Spatial Data. 2nd ed (2001), Physica Verlag
10. Müller, W.G., Stehlík, M., 2007. Issues in the optimal design of computer simulation experiments. IFAS Research Report Nr. 26, http://www.ifas.jku.at/e2550/e2756/index_ger.html
11. Pázman, A., 2004. Correlated optimum design with parametrized covariance function: Justification of the use of the Fisher information matrix and of the method of virtual noise. Report # 5. Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien. http://epub.wu-wien.ac.at/wp/
12. In: Pham H. (Ed). Springer Handbook of Engineering Statistics (2006), Springer Verlag, London (Chapter 13, pp. 229-247)
13. Santner T.J., Williams B.J., and Notz W.I. The Design and Analysis of Computer Experiments. Springer Series in Statistics (2003)
14. Stehlík, M., 2004. Some properties of d-optimal designs for random fields with different variograms. Report #4 Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien. http://epub.wu-wien.ac.at/wp/
15. Stehlík, M., 2006. Some properties of exchange design algorithms under correlation. Working Paper Nr. 28, WU Wien: Research Report Series/ Department of Statistics and Mathematics. http://epub.wu-wien.ac.at/wp/
16. Stehlík M. D-optimal designs and equidistant designs for stationary processes. In: López-Fidalgo J., Rodríguez-Díaz J.M., and Torsney B. (Eds). Proc. mODa8 (2007) pp. 205-212
17. Stehlík, M., Rodríguez-Díaz, J.M., Müller, W.G., López-Fidalgo, J., 2007. Optimal allocation of bioassays in the case of parametrized covariance functions: An application in lung's retention of radioactive particles. TEST, in press (doi:10.1007/s11749-006-0022-x)
18. Xia G., Miranda M.L., and Gelfand A.E. Approximately optimal spatial design approaches for environmental health data. Environmetrics 17 (2006) 363-385
19. Ying Z. Maximum likelihood estimation of parameters under a spatial sampling scheme. The Annals of Statistics 21 3 (1993) 1567-1590
20. Zhu Z., and Stein M.L. Spatial sampling design for parameter estimation of the covariance function. Journal of Statistical Planning and Inference 134 2 (2005) 583-603
21. Zhang H., and Zimmerman D. Towards reconciling two asymptotic frameworks in spatial statistics. Biometrika 92 4 (2005) 921-936