Generalized Whittle Estimate For Nonstationary Spatial Data
AbstractThis paper considers analysis of nonstationary irregularly spaced data that may have multivariate observations. The nonstationarity we focus on here means a local dependency of parameters that describe covariance structures. Nonparametric and parametric ways to estimate the local dependency of the parameters are proposed by an extension of traditional periodogram for stationary time series to that for nonstationary spatial data We introduce locally stationary processes for which consistency of the estimators are proved as well as demonstrate empirical efficiency of the methods by simulated and real examples.
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Bibliographic InfoPaper provided by Graduate School of Economics and Management, Tohoku University in its series TERG Discussion Papers with number 305.
Length: 20 pages
Date of creation: May 2013
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-11-22 (All new papers)
- NEP-ECM-2013-11-22 (Econometrics)
- NEP-EFF-2013-11-22 (Efficiency & Productivity)
- NEP-GEO-2013-11-22 (Economic Geography)
- NEP-URE-2013-11-22 (Urban & Real Estate Economics)
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