Statistical Analysis of Aircraft Trajectories: a Functional Data Analysis Approach

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 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.

Original document

The different versions of the original document can be found in:

• https://hal-enac.archives-ouvertes.fr/hal-01799104,

https://hal-enac.archives-ouvertes.fr/hal-01799104/document,

https://hal-enac.archives-ouvertes.fr/hal-01799104/file/functional_pca_camera.pdf