Spectral methods for nonstationary spatial processes

Biometrika

Volumn 89, Issue 1, 2002, Pages 197-210

  Fuentes, Montserrat ^a  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

Anisotropy; Covariance; Edge effect; Fourier transform; Geostatistics; Kernel smoothing; Periodogram; Spatial statistics; Variogram

Indexed keywords

EID: 0042401905     PISSN: 00063444     EISSN: None     Source Type: Journal    
DOI: 10.1093/biomet/89.1.197     Document Type: Article

References (23)

1. AKAIKE, H. (1974). A new look at statistical model identification. IEEE Trans. Auto. Contr. AC-19, 716-22.
2. BLOOMFIELD, P. (2000). Fourier Analysis of Time Series, 2nd ed. New York: Wiley.
3. BRILLINGER, D. R. (1970). The frequency analysis of relations between stationary spatial series. In Proceedings of the Twelfth Biennial Seminar of the Canadian Mathematical Congress, Ed. R. Pyke, pp. 39-81. Montreal: Canadian Math. Congress.
4. BRILLINGER, D. R. (1975). Time Series: Data Analysis and Theory. San Francisco: Holden-Day.
5. CLARK, R. M. (1977). Non-parametric estimation of a smooth regression function. J. R. Statist. Soc. B 39, 107-13.
6. CONSTANTINE, A. G. & HALL, P. (1994). Characterizing surface smoothness via estimation of effective fractal dimension. J. R. Statist. Soc. B 56, 96-113.
7. CRESSIE, N. (1993). Statistics for Spatial Data, rev. ed. New York: Wiley.
8. FUENTES, M. (2001). A high frequency kriging approach for nonstationary environmental processes. Envirometrics 12, 469-83.
9. GUYON, X. (1982). Parameter estimation for a stationary process on a d-dimensional lattice. Biometrika 69, 95-105.
10. GUYON, X. (1992). Champs Aléatoires sur un Réseau. Paris: Masson.
11. HAAS, T. C. (1995). Local prediction of a spatio-temporal process with an application to wet sulfate deposition. J. Am. Statist. Assoc. 90, 1189-99.
12. JAGLOM, A. M. (1987). Correlation Theory of Stationary and Related Random Functions. New York: Springer-Verlag.
13. KITANIDIS, P. K. (1983). Statistical estimation of polynomial generalized covariance functions and hydrologic applications. Water Resour. Res. 19, 909-21.
14. LAHIRI, S. M., KAISER, M. K., CRESSIE, N. & HSU, N. J. (1999). Prediction of spatial cumulative distribution functions using subsampling. J. Am. Statist. Assoc. 94, 86-97.
15. MARDIA, K. V. & MARSHALL, R. J. (1984). Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71, 135-46.
16. MARDIA, K. V., KENT, J. T. & BIBBY, J. M. (1979). Multivariate Analysis. New York: Academic Press.
17. PAWITAN, Y. & O'SULLIVAN F. (1994). Nonparametric spectral density estimation using penalized Whittle likelihood. J. Am. Statist. Assoc. 89, 600-10.
18. RIPLEY, B. D. (1981). Spatial Statistics. New York: John Wiley.
19. ROSENBLATT, M. R. (1985). Stationary Sequences and Random Fields. Boston: Birkhäuser.
20. STEIN, M. L. (1995). Fixed-domain asymptotics for spatial periodograms. J. Am. Statist. Assoc. 90, 1277-88.
21. STEIN, M. L. (1999). Interpolation of Spatial Data: Some Theory for Kriging. New York: Springer-Verlag.
22. STEIN, S. K. (1967). Calculus in the First Three Dimensions. New York: McGraw Hill, Inc.
23. WHITTLE, P. (1954). On stationary processes in the plane. Biometrika 41, 434-49.