New distance measures: the route toward truly non-Gaussian geostatistics

Conference · Sun May 01 00:00:00 EDT 1988 · J. Int. Assoc. Math. Geol.; (United States)

OSTI ID:6288065

Journel, A G

The projection or minimum error norm algorithm does not require that the distance measure be a variogram. In non-Gaussian cases, the traditional variogram distance measure leading to minimization of an error variance offers no definite advantage. Other distance measures, more outlier-resistant than the variogram, are proposed which fulfill the condition of the projection theorem. The resulting minimum error norms provide the same data configurations ranking as traditionally obtained from kriging variances. A case study based on actual digital terrain data is presented.

• Research Organization: Stanford Univ., CA (USA)
• OSTI ID: 6288065
• Report Number(s): CONF-8704137-
• Journal Information: J. Int. Assoc. Math. Geol.; (United States), Vol. 20:4; Conference: MGUS '87, Redwood City, CA, USA, 13 Apr 1987
• Country of Publication: United States
• Language: English

Related Subjects

58 GEOSCIENCES
DISTANCE
MEASURE THEORY
GEOLOGIC DEPOSITS
KRIGING
BOUNDARY CONDITIONS
DATA ANALYSIS
DATA COVARIANCES
DATA PROCESSING
DIAGRAMS
HILBERT SPACE
LAKES
MAPPING
NEVADA
PROBABILISTIC ESTIMATION
PROJECTION OPERATORS
SCALARS
STATISTICAL MODELS
WEIGHTING FUNCTIONS
BANACH SPACE
FEDERAL REGION IX
FUNCTIONS
MATHEMATICAL MODELS
MATHEMATICAL OPERATORS
MATHEMATICAL SPACE
MATHEMATICS
NORTH AMERICA
PROCESSING
SPACE
STATISTICS
SURFACE WATERS
USA
580203* - Geophysics- Geophysical Survey Methods- (1980-1989)