Spatial modeling of regional variables

Journal of the American Statistical Association

Volumn 84, Issue 406, 1989, Pages 393-401

  Cressie, Noel ^a   Chan, Ngai H ^b  

^a IOWA STATE UNIVERSITY   (United States)

^b INDIANA UNIVERSITY   (United States)

Author keywords

Auto Gaussian; Auto Poisson; Large scale variation; Markov random field; Small scale variation; Sudden infant death syndrome

Indexed keywords

EID: 84934736252     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.1989.10478783     Document Type: Article

References (22)

1. Atkinson, D. (1978), “Epidemiology of Sudden Infant Death in North Carolina: Do Cases Tend to Cluster?” Study 16, North Carolina Department of Human Resources, Division of Health Services, Public Health Statistics Branch, Raleigh.
2. Besag, J. E. (1974), “Spatial Interaction and the Statistical Analysis of Lattice Systems” (with discussion), Journal of the Royal Statistical Society, Ser. B, 35, 192–236.
3. Clayton, D., and Kaldor, J. (1987), “Empirical Bayes Estimates of Age Standardized Relative Risks for Use in Disease Mapping,” Biometrics, 43, 671–681.
4. Cliff, A. D., and Ord, J. K. (1981), Spatial Processes: Models and Applications, London: Pion.
5. Cressie, N. (1985), “When Are Relative Variograms Useful in Geostatistics?” Journal of the International Association for Mathematical Geology, 17, 693–702.
6. —— (1986), “Kriging Nonstationary Data,” Journal of the American Statistical Association, 81, 625–634.
7. —— (in press), Statistics for Spatial Data, New York: John Wiley.
8. Cressie, N., and Chan, N. H. (1986), “Spatial Modeling of Regional Variables,” Preprint 86–54, Iowa State University, Statistical Laboratory.
9. Cressie, N., and Guo, R. (1987), “Mapping Variables,” in Proceedings of the National Computer Graphics Association Conference: Computer Graphics ‘87 (Vol. 3), McLean, VA: National Computer Graphics Association, pp. 521–530.
10. Cressie, N., and Read, T. R. C. (in press), “Spatial Data Analysis of Regional Counts,” Biometrical Journal, 31.
11. Emerson, J. D., and Hoaglin, D. C. (1983), “Analysis of Two-Way Tables by Medians,” in Understanding Robust and Exploratory Data Analysis, eds. D. C. Hoaglin, F. Mosteller, and J. W. Tukey, New York: John Wiley, pp. 166–210.
12. Fogerty, A. C., Ford, G. L., Willcox, M. E., and Clancy, S. L. (1984), “Liver Fatty Acids and the Sudden Infant Death Syndrome,” American Journal of Clinical Nutrition, 39, 201–208.
13. Giulian, G. G., Gilbert, E. F., and Moss, R. L. (1987), “Elevated Fetal Hemoglobin Levels in Sudden Infant Death Syndrome,” The New England Journal of Medicine, 316, 1122–1126.
14. Goldberg, J., and Stein, R. (1978), “Seasonal Variations in SIDS,” Lancet, 8080, 107.
15. Journel, A. G., and Huijbregts, C. J. (1978), Mining Geostatistics, London: Academic Press.
16. Kindermann, R., and Snell, J. L. (1980), Markov Random Fields and Their Applications, Providence, RI: American Mathematical Society.
17. McCullagh, P. (1983), “Quasi-Likelihood Functions,” The Annals of Statistics, 11, 59–67.
18. Ord, J. K. (1975), “Estimation Methods for Models of Spatial Interaction,” Journal of the American Statistical Association, 70, 120–126.
19. Peters, T. J., and Golding, J. (1986), “Prediction of Sudden Infant Death Syndrome: An Independent Evaluation of Four Scoring Methods,” Statistics in Medicine, 5, 113–126.
20. Steinschneider, A. (1972), “Prolonged Apnea and the Sudden Infant Death Syndrome: Clinical and Laboratory Observations,” Pediatrics, 50, 646–654.
21. Symons, M. J., Grimson, R. C., and Yuan, Y. C. (1983), “Clustering of Rare Events,” Biometrics, 39, 193–205.
22. Whittle, P. (1954), “On Stationary Processes on the Plane,” Biometrika, 41, 434–449.