Partially Observed Functional Data: The Case of Systematically Missing Parts

21 Nov 2017Dominik LieblStefan Rameseder

By using a detour via the fundamental theorem of calculus, we propose a new estimation procedure that allows the consistent estimation of the mean and covariance function from partially observed functional data under specific violations of the missing-completely-at-random assumption. The requirements of our estimation procedure can be tested in practice using a sequential multiple hypothesis test procedure... (read more)

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