Statistical Analysis of Aircraft Trajectories: a Functional Data Analysis Approach

Abstract : 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.
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Alldata 2017, The Third International Conference on Big Data, Small Data, Linked Data and Open Data, Apr 2017, Venice, Italy. pp.51-56/ISBN: 978-1-61208-457-2, 2017, ALLDATA 2017 Proceedings
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Contributeur : Florence Nicol <>
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Florence Nicol. Statistical Analysis of Aircraft Trajectories: a Functional Data Analysis Approach. Alldata 2017, The Third International Conference on Big Data, Small Data, Linked Data and Open Data, Apr 2017, Venice, Italy. pp.51-56/ISBN: 978-1-61208-457-2, 2017, ALLDATA 2017 Proceedings. 〈hal-01799104〉

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