A good approximation of the Gaussian likelihood of simultaneous autoregressive model which yields us an asymptotically efficient estimate of parameters

DOI10.1016/J.JSPI.2016.01.003zbMath1335.62142OpenAlexW2238057566MaRDI QIDQ254917

Ritei Shibata, Yuuki Rikimaru

Publication date: 8 March 2016

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2016.01.003

zbMATH Keywords

maximum likelihoodcirculant matrixsimultaneous autoregressive modelspatial processWhittle approximation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Random fields (60G60) Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10)

Cites Work

• Spectral and circulant approximations to the likelihood for stationary Gaussian random fields
• Modified Whittle estimation of multilateral models on a lattice
• A note on the asymptotic eigenvalues and eigenvectors of the dispersion matrix of a second-order Stationary Process on a d-dimensional Lattice
• Edge effects and efficient parameter estimation for stationary random fields
• Parameter estimation for a stationary process on a d-dimensional lattice
• ON STATIONARY PROCESSES IN THE PLANE

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