On unit roots for spatial autoregressive models

DOI10.1016/j.jmva.2006.08.001zbMath1102.62098OpenAlexW2127915006MaRDI QIDQ860343

Vygantas Paulauskas

Publication date: 9 January 2007

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2006.08.001

zbMATH Keywords

unit rootrandom fieldsautoregressive models

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Spatial models in economics (91B72)

Related Items (8)

Parameter estimation in a spatial unilateral unit root autoregressive model ⋮ On the variances of a spatial unit root model ⋮ A note on self-normalization for a simple spatial autoregressive model ⋮ Efficiency of the OLS estimator in the vicinity of a spatial unit root ⋮ POWER PROPERTIES OF INVARIANT TESTS FOR SPATIAL AUTOCORRELATION IN LINEAR REGRESSION ⋮ Asymptotic inference for unit roots in spatial triangular autoregression ⋮ On the least squares estimator in a nearly unstable sequence of stationary spatial AR models ⋮ Testing stability in a spatial unilateral autoregressive model

Cites Work

• Prediction theory and Fourier series in several variables
• Prediction theory and Fourier series in several variables. II
• Asymptotic inference for unit roots in spatial triangular autoregression
• Aggregation of space-time processes.
• Spatial autoregression model: strong consistency.
• Linear processes in function spaces. Theory and applications
• A Wold-like decomposition of two-dimensional discrete homogeneous random fields
• Gauss-Newton estimation of parameters for a spatial autoregression model
• First-order intrinsic autoregressions and the de Wijs process
• Intrinsic autoregressions and related models on the two-dimensional lattice
• THE VARIANCE OF AN INTEGRATED PROCESS NEED NOT DIVERGE TO INFINITY, AND RELATED RESULTS ON PARTIAL SUMS OF STATIONARY PROCESSES
• ON STATIONARY PROCESSES IN THE PLANE
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