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<p>Created page with &quot; == Abstract == International audience; In Functional Data Analysis, the underlying structure of a raw observation is functional and data are assumed to be sample paths from...&quot;</p> <p><b>New page</b></p><div><br /> == Abstract ==<br /> <br /> International audience; In Functional Data Analysis, the underlying structure of a raw observation is functional and data are assumed to be sample paths from a single stochastic process. When data considered are functional in nature thus infinite-dimensional, like curves or images, the multivariate statistical procedures have to be generalized to the infinite-dimensional case. By approximating random functions by a finite number of random score vectors, the Principal Component Analysis approach appears as a dimension reduction technique and offers a visual tool to assess the dominant modes of variation, pattern of interest, clusters in the data and outlier detection. A functional statistics approach is applied to univariate and multivariate aircraft trajectories.<br /> <br /> <br /> == Original document ==<br /> <br /> The different versions of the original document can be found in:<br /> <br /> * [https://hal-enac.archives-ouvertes.fr/hal-01799104 https://hal-enac.archives-ouvertes.fr/hal-01799104],<br /> : [https://hal-enac.archives-ouvertes.fr/hal-01799104/document https://hal-enac.archives-ouvertes.fr/hal-01799104/document],<br /> : [https://hal-enac.archives-ouvertes.fr/hal-01799104/file/functional_pca_camera.pdf https://hal-enac.archives-ouvertes.fr/hal-01799104/file/functional_pca_camera.pdf]</div>

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