Geostatistical simulation when the number of experimental data is small: an alternative paradigm
type: Item
instance of: scholarly article
title: Geostatistical simulation when the number of experimental data is small: an alternative paradigm
zbMATH Open document ID: 1365.86022
author: Mario Chica-Olmo
author: Eulogio Pardo-Igúzquiza
published in: Stochastic Environmental Research and Risk Assessment
publication date: 2008-11-17T00:00:00Z
Mathematics Subject Classification ID: 86A32
zbMATH DE Number: 5367089
zbMATH Keywords: variogram model parameters
zbMATH Keywords: uncertainty propagation
zbMATH Keywords: Fisher information matrix
zbMATH Keywords: ergodic fluctuations
describes a project that uses: GSLIB
MaRDI profile type: Publication
full work available at URL: s00477-007-0118-1
OpenAlex ID: W2036434356
cites work: Q4256209
cites work: Q4002793
cites work: Maximum-likelihood estimation for the mixed analysis of variance model
cites work: Probability and statistical inference. II
cites work: Estimating variogram uncertainty
cites work: Maximum likelihood estimation of models for residual covariance in spatial regression
cites work: Q3998435
DOI: 10.1007/S00477-007-0118-1
description: scientific article; zbMATH DE number 5367089