Modelling effects of spatial variability of saturated hydraulic conductivity on autocorrelated overland flow data: Linear mixed model approach

DOI10.1007/S00477-006-0099-5zbMath1169.62398OpenAlexW2015555885WikidataQ125723574 ScholiaQ125723574MaRDI QIDQ841892

Hannu Sirviö, Michael Bruen, Antti Taskinen

Publication date: 18 September 2009

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

Full work available at URL: https://doi.org/10.1007/s00477-006-0099-5

zbMATH Keywords

covariance structuremixed linear modelrandom coefficientspatial variation

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Applications of statistics to environmental and related topics (62P12) Monte Carlo methods (65C05)

Related Items (1)

Modelling effects of spatial variability of saturated hydraulic conductivity on autocorrelated overland flow data: Linear mixed model approach

Uses Software

• MIXED
• SASmixed

Cites Work

• Unnamed Item
• Modelling effects of spatial variability of saturated hydraulic conductivity on autocorrelated overland flow data: Linear mixed model approach
• Linear mixed models in practice: a SAS-oriented approach
• Computing Gaussian Likelihoods and Their Derivatives for General Linear Mixed Models

This page was built for publication: Modelling effects of spatial variability of saturated hydraulic conductivity on autocorrelated overland flow data: Linear mixed model approach