Mathematics – Statistics Theory
Scientific paper
2008-04-04
Annals of Statistics 2008, Vol. 36, No. 2, 719-741
Mathematics
Statistics Theory
Published in at http://dx.doi.org/10.1214/009053607000000893 the Annals of Statistics (http://www.imstat.org/aos/) by the Inst
Scientific paper
10.1214/009053607000000893
This paper presents a new approach to the estimation of the deformation of an isotropic Gaussian random field on $\mathbb{R}^2$ based on dense observations of a single realization of the deformed random field. Under this framework we investigate the identification and estimation of deformations. We then present a complete methodological package--from model assumptions to algorithmic recovery of the deformation--for the class of nonstationary processes obtained by deforming isotropic Gaussian random fields.
Anderes Ethan B.
Stein Michael L.
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