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
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
maximum likelihoodcirculant matrixsimultaneous autoregressive modelspatial processWhittle approximation
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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