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Multiresolution decomposition of areal count data

Flury, Roman; Furrer, Reinhard (2019). Multiresolution decomposition of areal count data. In: GRASPA 2019 Conference, Pescara, Italy, 15 January 2019 - 16 July 2019. Università degli Studi di Bergamo, 86-89.

Abstract

Multiresolution decomposition is commonly understood as a procedure to capture scale-dependent features in random signals. Such methods were first established for image processing andtypically rely on raster or regularly gridded data. In this article, we extend a particular multiresolutiondecomposition procedure to areal count data, i.e. discrete irregularly gridded data. More specifically,we incorporate in a new model concept and distributions from the so-called Besag–York–Mollié modelto include a priori demographical knowledge. These adaptions and subsequent changes in the com-putation schemes are carefully outlined below, whereas the main idea of the original multiresolutiondecomposition remains. Finally, we show the extension’s feasibility by applying it to oral cavity cancercounts in Germany.

Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
07 Faculty of Science > Institute for Computational Science
Dewey Decimal Classification:340 Law
610 Medicine & health
510 Mathematics
Language:English
Event End Date:16 July 2019
Deposited On:27 Sep 2021 12:34
Last Modified:20 Apr 2022 08:46
Publisher:Università degli Studi di Bergamo
Series Name:GRASPA Working papers
Number:2019
ISSN:2037-7738
ISBN:978-88-97413-34-9
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.6092/GRASPA19
Official URL:https://aisberg.unibg.it//handle/10446/146889
Related URLs:https://aisberg.unibg.it/handle/10446/6132?locale=en
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