Dynamic multi-resolution spatial models

Environmental and Ecological Statistics

Volumn 14, Issue 1, 2007, Pages 5-25

  Johannesson, Gardar ^a   Cressie, Noel ^b   Huang, Hsin Cheng ^c  

^a LAWRENCE LIVERMORE NATIONAL LABORATORY   (United States)

^b OHIO STATE UNIVERSITY   (United States)

^c INSTITUTE OF STATISTICAL SCIENCE   (Taiwan)

Author keywords

Bayesian models; Change of resolution Kalman filter; Spatio temporal prediction; Total column ozone; Tree structured model

Indexed keywords

BAYESIAN ANALYSIS; KALMAN FILTER; KRIGING; MODEL; OZONE; PREDICTION; REMOTE SENSING; SATELLITE DATA; SPATIAL RESOLUTION; SPATIOTEMPORAL ANALYSIS; STRATOSPHERE;

EID: 33847106856     PISSN: 13528505     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10651-006-0005-9     Document Type: Article

References (41)

1. Agresti A (1990) Categorical data analysis. Wiley, New York
2. Berliner LM, Wikle CK, Cressie N (2000) Long-lead prediction of Pacific SSTs via Bayesian dynamic modeling. J Clim 13:3953-3968
3. Brown PE, Karesen KF, Roberts GO, Tonellato S (2000) Blur-generated nonseparable space-time models. J R Stat Soc Ser B 62:847-860
4. Calder C, Holloman C, Higdon D (2002) Exploring space-time structure in ozone concentration using a dynamic process convolution model. In: Gatsonis C, Kass RE, Carriquiry A, Gelman A, Higdon D, Pauler DK, Verdinelli I (eds) Case studies in Bayesian statistics 6. Springer-Verlag, New York, pp 165-176
5. Cane MA, Kaplan A, Miller RN, Tang B, Hackert EC, Busalacchi AJ (1996) Mapping tropical Pacific sea level: Data assimilation via reduced state space Kalman filter. J Geophys Res 101:22599-22617
6. Carroll R, Chen R, George E, Li T, Newton H, Schmiediche H, Wang N (1997) Ozone exposure and population density in Harris county, Texas (with discussion). J Am Stat Assoc 92:392-415
7. Chou KC, Willsky AS, Nikoukhah R (1994) Multiscale systems, Kalman filters, and Riccati equations. IEEE Trans Autom Control. 39:479-492
8. Cressie N (1993) Statistics for spatial data (revised edition). Wiley, New York
9. Cressie N (1994) Comment on "An approach to statistical spatial-temporal modeling of meteorological fields" by M.S. Handcock and J.R. Wallis. J Am Stat Assoc 89:379-382
10. Cressie N (2002) Variogram estimation. In: El-Shaarawi AH, Piegorsch WW (eds) Encyclopedia of environmetrics, vol 4. Wiley, New York, pp 2316-2321
11. Cressie N, Huang H-C (1999) Classes of nonseparable, spatio-temporal stationary covariance functions. J Am Stat Assoc 94:1330-1340
12. Cressie N, Wikle CK (2002) Space-time Kalman filter. In: El-Shaarawi AH, Piegorsch WW (eds) Encyclopedia of environmetrics, vol. 4. Wiley, New York, pp 2045-2049
13. de Iaco S, Myers DE, Posa D (2001) Space-time analysis using a general product-sum model. Stat Probab Lett 52:21-28
14. Gelfand AE, Ghosh S, Knight J, Sirmans C (1998) Spatio-temporal modeling of residual sales data. J Bus Econ Stat 16:312-321
15. Gelpke V, Künsch HR (2001) Estimation of motion from sequences of images. In: Moore M (ed) SpMtial statistics: methodological aspects and applications. Springer lecture notes in statistics, vol 159. Springer-Verlag, New York, pp 141-167
16. Gneiting T (2002) Nonseparable, stationary covariance functions for space-time data. J Am Stat Assoc 97:590-600
17. Guttorp P, Sampson PD, Newman K (1992) Nonparametric estimation of spatial covariance with application to monitoring network evaluation. In: Walden A, Guttorp P (eds) Statistics in environmental and earth sciences. Edward Arnold, London, pp 39-51
18. Handcock MS, Wallis JR (1994) An approach to statistical spatial-temporal modeling of meteorological fields. J Am Stat Assoc 89:368-378
19. Hartfield MI, Gunst RF (2003) Identification of model components for a class of continuous spatiotemporal models. J Agric Biol Environ Stat 8:105-121
20. Harville DA (1997) Matrix algebra from a statistician's perspective. Springer-Verlag, New York
21. Haslett J, Raftery AE (1989) Space-time modeling with long-memory dependence: Assessing ireland's wind power resource. Appl Stat 38:1-21
22. Huang H-C (1997) Spatial modeling using graphical Markov models and wavelets. Ph.D. thesis, Department of Statistics, Iowa State University
23. Huang H-C, Cressie N (1996) Spatio-temporal prediction of snow water equivalent using the Kalman filter. Comput Stat Data Anal 22:159-175
24. Huang H-C, Cressie N (2001) Multiscale graphical modeling in space: applications to command and control. In: Moore M (ed) Spatial statistics: Methodological aspects and some applications. Springer lecture notes in statistics, vol 159. Springer-Verlag, New York, pp 83-113
25. Huang H-C, Hsu N-J (2004) Modeling transport effects on ground-level ozone using a non-stationary space-time model. Environmetrics 15:251-268
26. Huang H-C, Cressie N, Gabrosek J (2002) Fast, resolution-consistent spatial prediction of global processes from satellite data. J Comput Graph Stat 11:63-88
27. Huerta G, Sanso B, Stroud JR (2004) A spatio-temporal model for Mexico City ozone levels. Appl Stat 53:231-248
28. Johannesson G (2003) Multi-resolution statistical modeling in space and time with application to remote sensing of the environment. Ph.D. thesis, Department of Statistics, The Ohio State University
29. Johannesson G, Cressie N (2004) Variance-covariance modeling and estimation for multi-resolution spatial models. In: Sanchez-Vila X, Carrera J, Gómez-Hernández J (eds) geoENV IV - geostatistics for environmental applications. Kluwer Academic Publishers, Dordrecht, Netherlands, pp 319-330
30. Jones RH, Zhang Y (1997) Models for continuous stationary space-time processes. In: Gregoire TG et al. (eds) Modelling longitudinal and spatially correlated data. Springer lecture notes in statistics, vol 122. Springer-Verlag, New York, pp 289-298
31. Kolaczyk ED, Huang H (2001) Multiscale statistical models for hierarchical spatial aggregation. Geogr Anal 33:95-118
32. Kyriakidis PC, Journel AG (1999) Geostatistical space-time models: A review. Math Geol 31:651-684
33. Mardia K, Goodall C, Redfern E, Alonso F (1998) The kriged Kalman filter (with discussion). Test 7:217-285
34. McCulloch CE, Searle SR (2001) Generalized, linear, and mixed models. Wiley, New York
35. Meiring W, Guttorp P, Sampson PD (1998) Space-time estimation of grid-cell hourly ozone levels for assessment of a deterministic model. Environ Ecol Stat 5:197-222
36. Stein M (2005) Space-time covariance functions. J Am Stat Assoc 100:310-321
37. Stroud JR, Müller P, Sansó, B (2001) Dynamic models for spatiotemporal data. J R Stat Soc Ser B 63:673-689
38. Wahba G (1990) Spline models for observational data. Society for Industrial and Applied Mathematics, Philadelphia, PA
39. Waller L, Carlin B, Xia H, Gelfand A (1997) Hierarchical spatio-temporal mapping of disease rates. J Am Stat Assoc 92:607-617
40. Wikle CK, Cressie N (1999) A dimension-reduced approach to space-time Kalman filtering. Biometrika 86:815-829
41. Wikle CK, Berliner M, Cressie N (1998) Hierarchical Bayesian space-time models. Environ Ecol Stat 5:117-154