Statistics for Spatial Data

Cressie, N. A. C. (1993). Statistics for Spatial Data. Wiley.

Type

Book

Intellectual base

Textbook

Year

1993

DOI

10.1002/9781119115151

ISBN

9780471002550

DOI registrant

Wiley

Link

https://doi.org/10.1002/9781119115151

Cited by

3 citations across 3 artifacts.

Each citation links to the sentence it supports in the citing article.

Domain-specific

• Kriging
  • Kriging is a best-linear-unbiased spatial prediction method whose weights derive from a modeled covariance or variogram under stated mean assumptions.
• Variogram
  • Its role structure includes support, lag, stationarity assumptions, directional dependence, estimator bins, an admissible fitted model, and features such as nugget, sill, and range.

Mechanisms

• Adaptive Sensor Mesh
  • This is the same logic that geostatistics formalizes as variance-driven optimal sampling — put the next observation where the estimation variance is largest.

    This sourceFormalizes variance-driven spatial sampling by placing a next observation where kriging estimation variance is greatest.

Verification

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Does it back the claim? Not recorded. Neither this nor any other of the 3 citations of this work carries a recorded support check.

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Registry ID ref:ce19fa422131 · see in the full table