Bayesian Spatial Inversion and Conjugate Selection Gaussian Prior Models

DOI10.1137/19M1302995zbMath1464.62289arXiv1812.01882OpenAlexW3156479501MaRDI QIDQ4995110

Kjartan Rimstad, Henning Omre

Publication date: 23 June 2021

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1812.01882

zbMATH Keywords

inverse problemsspatial predictionconditional simulationseismic inversionspatial inference

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11)

Related Items (2)

A skew-normal spatial simultaneous autoregressive model and its implementation ⋮ Ensemble-based seismic and production data assimilation using selection Kalman model

Uses Software

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Cites Work

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• A Bayesian level set method for geometric inverse problems
• Shape mixtures of multivariate skew-normal distributions
• Computation of multivariate normal and \(t\) probabilities
• A Bayesian prediction using the skew Gaussian distribution.
• Hierarchical Bayesian level set inversion
• Latent Gaussian random field mixture models
• Geostatistics
• Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities
• The multivariate skew-normal distribution
• Inverse Problem Theory and Methods for Model Parameter Estimation
• Objective Bayesian Analysis of Skew‐t Distributions
• Statistics for Spatial Data
• A unified view on skewed distributions arising from selections
• A New Spatial Skew-Normal Random Field Model
• Statistical Analysis and Modelling of Spatial Point Patterns
• The Skew-normal Distribution and Related Multivariate Families*

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