Estimation and selection for spatial confounding regression models

DOI10.1080/03610926.2021.1934025OpenAlexW3169525156MaRDI QIDQ5875272

Chun-Shu Chen, Hong-Ding Yang, Y. H. Chiou

Publication date: 3 February 2023

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2021.1934025

zbMATH Keywords

variable selectionspatial predictionmean squared prediction errorrestricted spatial regressionconditional information criterion

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• FRK

Cites Work

• Unnamed Item
• The importance of scale for spatial-confounding bias and precision of spatial regression estimators
• Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love
• Statistical Methods for Spatial Data Analysis
• Fixed Rank Kriging for Very Large Spatial Data Sets
• Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models
• Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease‐Mapping Models
• Estimation and Prediction in the Presence of Spatial Confounding for Spatial Linear Models
• Conditional Akaike information for mixed-effects models
• Restricted spatial regression in practice: geostatistical models, confounding, and robustness under model misspecification

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