Estimation of the spatial covariance in Universal Kriging: Application to forest inventory

Environmental and Ecological Statistics

Volumn 7, Issue 3, 2000, Pages 263-284

  Mandallaz, D ^a  

^a ETH ZURICH   (Switzerland)

Author keywords

Kriging; Least squares; Restricted maximum likelihood; Two phase two stage sampling

Indexed keywords

COVARIANCE ANALYSIS; FOREST INVENTORY; KRIGING; STATISTICAL ANALYSIS;

EID: 0033676256     PISSN: 13528505     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1009619117138     Document Type: Article

References (32)

1. Fitting variograms models by weighted least squares
2. The asymptotic distribution of reml estimators
3. Asymptotics for reml estimation of spatial covariance parameters
4. Using geostatistics for forest inventory with air cover: An example
5. Model-based geostatistics (with discussion)
6. Central limit theorem for quadratic forms in random variables having long range dependence
7. Bayesian spatial prediction
8. A bayesian analysis of kriging
9. Topics in spatial statistics
10. When do we need a trend model in kriging
11. Minimum variance unbiased quadratic estimation of covariances of regionalized variables
12. Forest inventory with optimal two-phase, two-stage sampling schemes based on the anticipated variance
13. Maximum likelihood estimation of models for residual covariance in spatial regression
14. The intrinsic random functions and their applications
15. To be or not to be ... stationary? That is the question
16. Estimation the area affected by phosphorus runoff in an everglades wetland: A comparison of universal and Bayesian kriging
17. Minimum variance quadratic unbiased estimation of variance components
18. Minimum norm quadratic unbiased estimation of spatial variograms
19. Asymptotic properties of minimum norm quadratic estimators of the covariance function of a gaussian random field
20. A monte carlo comparison of spatial variogram estimators and corresponding kriging predictors