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• W3008137344 abstract "Irregular functional data in which densely sampled curves are observed over different ranges pose a challenge for modeling and inference, and sensitivity to outlier curves is a concern in many applications. This paper investigates a class of robust M-estimators for partially observed functional data, modeling irregular structure using a missing data framework. We derive asymptotic normality of functional M-estimator under the proposed framework and show root-$n$ rates of convergence. Furthermore, we propose a class of functional trend tests to find significant directions in the trend of location. For the implementation of the inferential test, we adopt a joint bootstrap approach. The performance is demonstrated in simulations and application to data from quantitative ultrasound analysis." @default.
• W3008137344 created "2020-03-06" @default.
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• W3008137344 date "2020-02-20" @default.
• W3008137344 modified "2023-09-27" @default.
• W3008137344 title "Robust M-estimation for Partially Observed Functional Data" @default.
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• W3008137344 hasPublicationYear "2020" @default.
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