3.8 Article

Robust functional principal components for sparse longitudinal data

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Summary: This paper aims to develop a parsimonious representation of longitudinal data through a linear combination of smooth functions, while being resistant to various types of contamination and incomplete data. Two approaches are proposed, one meeting specific requirements and the other being a simple and fast estimator. Experiments show that the simple estimator outperforms competitors with complete data, while the MM estimator is competitive for incomplete data.

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