Extrinsic Data Analysis on Object Spaces

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• Mihaela Pricop-Jeckstadt (University Politehnica of Bucharest)
• Wednesday 07 May 2025, 14:30-15:00
• Seminar Room 1, Newton Institute.

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RCLW01 - Uncertainty in multivariate, non-Euclidean, and functional spaces: theory and practice

This is work on complex data, jointly with Vic Patragenaru and Robert L. Paige. The talk aims to develop a methodology for object oriented data analysis based on chord distance on manifolds. Previous work showed that the resulting extrinsic statistical techniques for independent samples of two-dimensional image data have greater statistical power than comparable statistical techniques which ignore directional information. In this work we develop a novel matched pairs test for two-dimensional oriented projective shapes and apply it on matched sets of images. Our novel matched pairs test, with optimally paired images, is highly statistically significant while the unpaired test fails to find evidence for a statistical effect.   Authors   Vic Patrangenaru FSU , USA vic@stat.fsu.edu   Robert Paige Missouri University of Science and Technology, USA paigero@mst.edu     Mihaela Pricop-Jeckstadt (speaker) The National University for Science and Technology POLITEHNICA of Bucharest, Romania Mihaela.Pricop@upb.ro

This talk is part of the Isaac Newton Institute Seminar Series series.

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