Dimitriou-Fakalou, C. (2010) Statistical Inference for Spatial Auto-Linear Processes. Journal of Statistical Theory and Practice, 4 (3). pp. 345-365. ISSN 1559-8608.
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A new class of simultaneous auto-models that clothe naturally the weak dependence of spatial processes, is presented. the parameeters of the so-called auto-linear process are best linear prediction coefficients. With a finite transformation on the original process, the new process has auto-correlations equal to the parameters of interest. New method of moments estimators are proposed and they are consistent and asymptotically normal. Their variance matrix may be written down explicitly in terms of the auto-linear parameters and the result is distribution free. A simulation study and a data example are presented to support the use of the auto-linear model for spatial processes provding convenience for the statistical inference.
|Uncontrolled keywords:||Auto-linear process, Bartlett's fromula, Linear predictor, Spectral density|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics|
|Depositing User:||Chrysoula Dimitriou Fakalou|
|Date Deposited:||10 Oct 2012 12:21|
|Last Modified:||12 Feb 2013 09:02|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/31483 (The current URI for this page, for reference purposes)|
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