This work aims at performing Functional Principal Components Analysis (FPCA) thanks to Horvitz-Thompson estimators when the curves are collected with survey sampling techniques. Linearization approaches based on the infiuence function allow us to derive estimators of the asymptotic variance of the eigenelements of the FPCA. The method is illustrated with simulations which confirm the good properties of the linearization technique.
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Cardot, H., Chaouch, M., Goga, C., Labruère, C. (2008). Functional Principal Components Analysis with Survey Data. In: Functional and Operatorial Statistics. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2062-1_16
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DOI: https://doi.org/10.1007/978-3-7908-2062-1_16
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2061-4
Online ISBN: 978-3-7908-2062-1
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