Spatial statistical models that use flow and stream distance

Environmental and Ecological Statistics

Volumn 13, Issue 4, 2006, Pages 449-464

  Ver Hoef, Jay M ^a,c   Peterson, Erin ^b   Theobald, David ^b  

^a ALASKA DEPARTMENT OF FISH AND GAME   (United States)

^b Department of Environmental and Radiological Health Sciences   (United States)

^c NOAA National Marine Mammal Laboratory   (United States)

Author keywords

Block kriging; Geostatistics; Stream networks; Valid autocovariances; Variogram

Indexed keywords

DATA SET; GEOSTATISTICS; KRIGING; MAXIMUM LIKELIHOOD ANALYSIS; NUMERICAL MODEL; SPATIAL ANALYSIS; STATISTICAL DATA; STREAMFLOW; VARIOGRAM;

EID: 33750575909     PISSN: 13528505     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10651-006-0022-8     Document Type: Article

References (21)

1. Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Csaki F (eds) Second International Symposium on Information Theory. Akademiai Kiado, Budapest, pp 267-281
2. RP Barry JM Ver Hoef 1996 Blackbox kriging: Spatial prediction without specifying the variogram J Agricult Biol Environ Stat 1 297-322 10.2307/ 1400521
3. J-P Chiles P Delfiner 1999 Geostatistics: Modeling spatial uncertainty John Wiley and Sons New York 695
4. N Cressie 1993 Statistics for spatial data, revised edition John Wiley and Sons New York 900
5. N Cressie JJ Majure 1997 Spatio-temporal statistical modeling of livestock waste in streams J Agricult Biol Environ Stat 2 24-47 10.2307/ 1400639
6. N Cressie M Pavlicova 2002 Calibrated spatial moving average simulations Stat Model 2 267-279 10.1191/1471082x02st035oa
7. Curriero F (1996) The use of non-euclidean distance in geostatistics. Ph.D. Thesis, Kansas State University
8. CL Dent NB Grimm 1999 Spatial heterogeneity of stream water nutrient concentrations over successional time Ecology 80 2283-2298 10.2307/176910
9. M Fuentes 2002 Spectral methods for nonstationary spatial processes Biometrika 89 197-210 10.1093/biomet/89.1.197
10. B Gardner PJ Sullivan AJ Lembo Jr 2003 Predicting stream temperatures: geostatistical model comparison using alternative distance metrics Can J Fish Aquat Sci 60 344-351 10.1139/f03-025
11. D Higdon 1998 A process-convolution approach to modelling temperatures in the North Atlantic Ocean Environ Ecol Stat 5 173-190 10.1023/ A:1009666805688
12. Higdon D, Swall J, Kern J (1999) Non-stationary spatial modeling. In Bayesian statistics 6, Oxford Univ Press, Oxford 761-768
13. RC Littell RC Milliken WW Stroup R Wolfinger 1996 SAS system for mixed models SAS publishing Cary, NC 656
14. LS Little D Edwards DE Porter 1997 Kriging in estuaries: As the crow flies, or as the fish swims J Exp Mar Biol Ecol 213 1-11 10.1016/ S0022-0981(97)00006-3
15. SL Rathbun 1998 Spatial modeling in irregularly shaped regions: Kriging estuaries Environmetrics 9 109-129 1:CAS:528:DyaK1cXislaku78%3D 10.1002/ (SICI)1099-095X(199803/04)9:2<109::AID-ENV279>3.0.CO;2-L
16. G Schwarz 1978 Estimating the dimension of a model Ann Stat 6 461-464
17. RA Smith GE Schwarz RB Alexander 1997 Regional interpretation of water-quality monitoring data Water Resour Res 33 2781-2798 1:CAS:528:DyaK2sXotVensbY%3D 10.1029/97WR02171
18. Torgersen CE, Gresswell RE, Bateman DS (2004) Pattern detection in stream networks: Quantifying spatial variability in fish distribution. In: Nishida, T. (ed), Proceedings of the Second Annual International Symposium on GIS/Spatial Analyses in Fishery and Aquatic Sciences. Fishery GIS Research Group, Saitama, Japan
19. JM Hoef Ver RP Barry 1998 Constructing and fitting models for cokriging and multivariable spatial prediction J Stat Planning Inference 69 273-294
20. JM Hoef Ver N Cressie RP Barry 2004 Flexible spatial models for kriging and cokriging using moving averages and the fast Fourier transform (FFT) J Comput Graphical Stat 13 265-282 10.1198/1061860043498
21. LL Yuan 2004 Using spatial interpolation to estimate stressor levels in unsampled streams Environ Monit Assess 94 23-38 15141444 10.1023/ B:EMAS.0000016877.52279.05