On Selection of Spatial Linear Models for Lattice Data

DOI10.1111/j.1467-9868.2010.00739.xzbMath1411.62275OpenAlexW1927594589MaRDI QIDQ4632636

Jun Zhu, Hsin-Cheng Huang, Perla E. Reyes

Publication date: 30 April 2019

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9868.2010.00739.x

zbMATH Keywords

model selectionspatial statisticsvariable selectionsimultaneous autoregressive modelpenalized likelihoodconditional autoregressive model

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to environmental and related topics (62P12) Point estimation (62F10)

Related Items

Variable selection of partially linear varying coefficient spatial autoregressive model, The signature of endemic populations in the spread of mountain pine beetle outbreaks, The Bayesian group Lasso for confounded spatial data, Automatic variable selection for semiparametric spatial autoregressive model, Estimation of nonparametric additive models with high order spatial autoregressive errors, Penalty and related estimation strategies in the spatial error model, Recognition and variable selection in sparse spatial panel data models with fixed effects, High dimensional classification for spatially dependent data with application to neuroimaging, On a Semiparametric Data‐Driven Nonlinear Model with Penalized Spatio‐Temporal Lag Interactions, Estimation and Inference for Generalized Geoadditive Models, Variable selection for spatial Poisson point processes via a regularization method, On estimation and selection of autologistic regression models via penalized pseudolikelihood, Variable selection for spatial semivarying coefficient models, Bayesian model selection in spatial lattice models, Spatial Homogeneity Pursuit of Regression Coefficients for Large Datasets, Sparse spatially clustered coefficient model via adaptive regularization, Comparing and selecting spatial predictors using local criteria, Rejoinder on: ``Comparing and selecting spatial predictors using local criteria