Spectral estimation of a structural thin-plate smoothing model
Computational Statistics & Data Analysis, 2008, vol. 53, issue 1, 189-195
A nonstationary structural spatial model that explicitly sets the data to evolve across a rectangular lattice constrained by second-order smoothing restrictions is presented. The model exemplifies the concept of model-based spatial smoothing and, in particular, it provides a rationale for the popular discrete thin-plate smoothing method. It is further shown how to use a frequency-domain approach to estimate the spatial model via maximum likelihood. In essence, the approach allows both dimensions to be treated separately from each other so that the computational burden for the estimation of two-dimensional models is dramatically reduced both in terms of the computing time and the memory required. Besides, this spectral approach allows straightforward construction of analytic derivatives and an expression for the asymptotic variance of the estimated smoothing parameter is derived with which to construct confidence intervals. Some numerical Monte-Carlo evidence and one example illustrate the results given.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:53:y:2008:i:1:p:189-195
Access Statistics for this article
Computational Statistics & Data Analysis is currently edited by S.P. Azen
More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Haili He ().