On Hypotheses Testing for the Selection of Spatio-Temporal Models

DOI10.1111/j.1467-9892.2006.00488.xzbMath1115.62081OpenAlexW2114679438MaRDI QIDQ3440769

T. Subba Rao, Anna Mónica C. Antunes

Publication date: 29 May 2007

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.2006.00488.x

zbMATH Keywords

likelihood ratio testvector autoregressionnon-nested hypothesesKullback-Leibler information gainspatial-time autoregression

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: hypothesis testing (62M07)

Related Items (5)

Modeling Interval Time Series with Space–Time Processes ⋮ Testing for poolability of the space-time autoregressive moving-average model ⋮ Statistics for Spatio‐Temporal Data ⋮ Optimal spatial aggregation of space-time models and applications ⋮ Clustering of interval time series

Cites Work

• A Three-Stage Iterative Procedure for Space-Time Modeling
• Regularity conditions for Cox's test of non-nested hypotheses
• Statistical inference in non-nested econometric models
• Time series: theory and methods.
• Modelling Daily Multivariate Pollutant Data at Multiple Sites
• Estimation and Identification of Space-Time ARMAX Models in the Presence of Missing Data
• A dimension-reduced approach to space-time Kalman filtering

This page was built for publication: On Hypotheses Testing for the Selection of Spatio-Temporal Models