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Title: Functional data analysis and censoring Authors:  Stanislav Nagy - Charles University (Czech Republic)
David Kraus - Masaryk University (Czech Republic) [presenting]
Abstract: Functional data analysis is often complicated by the fact that the information collected about the curves is distorted due to incomplete, fragmentary, discrete, noisy or otherwise imperfect observation. We focus on censoring. We discuss the estimation of characteristics of the distribution of functional data and the prediction of functional observations.