Geostatistical simulation when the number of experimental data is small: an alternative paradigm

DOI10.1007/s00477-007-0118-1zbMath1365.86022OpenAlexW2036434356MaRDI QIDQ954699

Mario Chica-Olmo, Eulogio Pardo-Igúzquiza

Publication date: 17 November 2008

Published in: Stochastic Environmental Research and Risk Assessment (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00477-007-0118-1

zbMATH Keywords

Fisher information matrixuncertainty propagationergodic fluctuationsvariogram model parameters

Mathematics Subject Classification ID

Geostatistics (86A32)

Uses Software

• GSLIB

Cites Work

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• Estimating variogram uncertainty
• Probability and statistical inference. II
• Maximum likelihood estimation of models for residual covariance in spatial regression
• Maximum-likelihood estimation for the mixed analysis of variance model

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