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Graph-Based Spatial Segmentation of Health-Related Areal Data

Abstract : Smoothing is often used to improve the readability and interpretability of noisy areal data. However there are many instances where the underlying quantity is discontinuous. In this case, specific methods are needed to estimate the piecewise constant spatial process. A well-known approach in this setting is to perform segmentation of the signal using the adjacency graph, as does the graph-based fused lasso. But this method does not scale well to large graphs. This article introduces a new method for piecewise-constant spatial estimation that (i) is fast to compute on large graphs and (ii) yields sparser models than the fused lasso (for the same amount of regularization), giving estimates that are easier to interpret.
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https://hal.archives-ouvertes.fr/hal-03474990
Contributor : Vivien Goepp Connect in order to contact the contributor
Submitted on : Friday, May 27, 2022 - 11:09:35 AM
Last modification on : Tuesday, October 18, 2022 - 11:02:09 AM