Bootstrapped models for intrinsic random functions

Conference · Mon Aug 01 04:00:00 EDT 1988 · J. Int. Assoc. Math. Geol.; (United States)

OSTI ID:6288095

Campbell, K

Use of intrinsic random function stochastic models as a basis for estimation in geostatistical work requires the identification of the generalized covariance function of the underlying process. The fact that this function has to be estimated from data introduces an additional source of error into predictions based on the model. This paper develops the sample reuse procedure called the bootstrap in the context of intrinsic random functions to obtain realistic estimates of these errors. Simulation results support the conclusion that bootstrap distributions of functionals of the process, as well as their kriging variance, provide a reasonable picture of variability introduced by imperfect estimation of the generalized covariance function.

• Research Organization: Los Alamos National Lab., NM (USA)
• OSTI ID: 6288095
• Report Number(s): CONF-8704137-
• Conference Information: Journal Name: J. Int. Assoc. Math. Geol.; (United States) Journal Volume: 20:6
• Country of Publication: United States
• Language: English

Related Subjects

58 GEOSCIENCES
580203* -- Geophysics-- Geophysical Survey Methods-- (1980-1989)
ACCURACY
ALGORITHMS
COMPUTERIZED SIMULATION
DATA ANALYSIS
DATA COVARIANCES
DATA PROCESSING
FUNCTIONS
GEOLOGIC DEPOSITS
GEOPHYSICAL SURVEYS
INTERPOLATION
KRIGING
MATHEMATICAL LOGIC
MATHEMATICAL MODELS
MATHEMATICS
METRICS
NUMERICAL SOLUTION
PROBABILISTIC ESTIMATION
PROCESSING
RANDOMNESS
SAMPLING
SIMULATION
STATISTICAL MODELS
STATISTICS
SURVEYS