Optimal spatial prediction for non-negative spatial processes using a phi-divergence loss function

DOI10.1007/978-3-031-04137-2_17zbMath1497.62252OpenAlexW4283585853MaRDI QIDQ2087081

David Gunawan, Alan R. Pearse, Noel Cressie

Publication date: 26 October 2022

Full work available at URL: https://doi.org/10.1007/978-3-031-04137-2_17

zbMATH Keywords

decision theoryloss functiongeostatisticspower divergence measureunconditional risk

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Geostatistics (86A32)

Uses Software

• Gstat
• gstat

Cites Work

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• Statistical decision theory and Bayesian analysis. 2nd ed
• Goodness-of-fit statistics for discrete multivariate data
• Model checking in loglinear models using \(\phi\)-divergences and MLEs
• Bayesian Estimation and Prediction Using Asymmetric Loss Functions
• Statistics for Spatial Data