Gaussian random field's anisotropy using excursion sets
Jean-Marc Aza\"is, Federico Dalmao, Yohann De Castro

TL;DR
This paper develops a novel, model-agnostic method to detect and estimate anisotropy in stationary random fields from single excursion set realizations, with applications to cosmic microwave background data.
Contribution
It generalizes the contour method to arbitrary dimensions and introduces a new statistical test for isotropy that does not require covariance knowledge.
Findings
The proposed test is well-calibrated and more powerful than existing methods.
Anisotropy parameters can be robustly estimated from normal vectors along excursion set boundaries.
Application to Planck CMB data demonstrates practical utility.
Abstract
This paper addresses the problem of detecting and estimating the anisotropy of a stationary real-valued random field from a single realization of one of its excursion sets. This setting is challenging as it relies on observing a binary image without prior knowledge of the field's mean, variance, or the specific threshold value. Our first contribution is to propose a generalization of Caba\~na's contour method to arbitrary dimensions by analyzing the Palm distribution of normal vectors along the excursion set boundaries. We demonstrate that the anisotropy parameters can be recovered by solving a smooth and strongly convex optimization problem involving the eigenvalues of the empirical covariance matrix of these normal vectors. Our second main contribution is a new, model-agnostic statistical test for isotropy in dimension two. We introduce a statistic based on the contour method…
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Taxonomy
TopicsPoint processes and geometric inequalities · Soil Geostatistics and Mapping · Synthetic Aperture Radar (SAR) Applications and Techniques
