Coregionalized Single- and Multiresolution Spatially Varying Growth Curve Modeling with Application to Weed Growth

DOI10.1111/j.1541-0420.2006.00535.xzbMath1111.62115OpenAlexW2090648474WikidataQ51933176 ScholiaQ51933176MaRDI QIDQ3436535

Sudipto Banerjee, Gregg A. Johnson

Publication date: 11 May 2007

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2006.00535.x

zbMATH Keywords

Markov chain Monte CarloKronecker productsmultiresolution modelsnonseparable modelscoregionalizationnonstationary modelsmultivariate Gaussian processes

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Signal detection and filtering (aspects of stochastic processes) (60G35) Inference from stochastic processes (62M99)

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Uses Software

• spBayes

Cites Work

• Interpolation of spatial data. Some theory for kriging
• Nonstationary multivariate process modeling through spatially varying coregionalization
• Analyzing Variety by Environment Data Using Multiplicative Mixed Models and Adjustments for Spatial Field Trend
• Model-Based Geostatistics
• Directional Rates of Change Under Spatial Process Models
• Bayesian Measures of Model Complexity and Fit
• Parameterization and Bayesian Modeling
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