Infill asymptotics for a stochastic process model with measurement error

Statistica Sinica

Volumn 10, Issue 1, 2000, Pages 141-156

  Chen, Huann Sheng ^a   Simpson, Douglas G ^b   Ying, Zhiliang ^c  

^a MICHIGAN TECHNOLOGICAL UNIVERSITY   (United States)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^c RUTGERS UNIVERSITY   (United States)

Author keywords

Asymptotic normality; Consistency; Covariance; Gaussian process; Identifiability; Maximum likelihood estimator; Measurement error; Rate of convergence

Indexed keywords

EID: 0034383430     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (11)

1. Cressie, N. (1991). Statistics for Spatial Data. Wiley, New York.
2. Ibragimov, I. A. and Rozanov, Y. A. (1978). Gaussian Random Processes. Springer, New York.
3. Mardia, K. V. and Marshall, R. J. (1984). Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71, 135-146.
4. Ortega, J. M. (1987). Matrix Theory: A Second Course. Plenum Press, New York.
5. Ripley, B. D. (1981). Spatial Statistics. Wiley, New York.
6. Sacks, J., Schiller, S. B. and Welch, W. J. (1989). Designs for computer experiments. Technometrics 31, 41-47.
7. Sacks, J., Welch, W. J., Mitchell, T. J. and Wynn, H. P. (1989). Design and analysis of computer experiments. Statist. Sci. 4, 409-435.
8. Stein, M. L. (1990). A comparison of generalized cross validation and modified maximum likelihood for estimation the parameters of a stochastic process. Ann. Statist. 18, 1139-1157.
9. Stein, M. L. (1993). Spline smoothing with an estimated order parameter. Ann. Statist. 21, 1522-1544.
10. Ying, Z. (1991). Asymptotic properties of a maximum likelihood estimator with data from a Gaussian process. J. Multivar. Anal. 36, 280-296.
11. Ying, Z. (1993). Maximum likelihood estimation of parameters under a spatial sampling scheme. Ann. Statist. 21, 1567-1590.