Proposes a Markov transform and estimator for the covariance kernel in functional data under Markov constraints, with a new test for the Markov property in continuous graphical models.
Covariance operator estimation via adaptive threshold- ing
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Functional multi-reference alignment is addressed by extending Kotlarski's deconvolution formula to general dimensions and signals with vanishing Fourier transforms.
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Inference for Functional Data under Markov Constraints
Proposes a Markov transform and estimator for the covariance kernel in functional data under Markov constraints, with a new test for the Markov property in continuous graphical models.
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Functional Multi-Reference Alignment via Deconvolution
Functional multi-reference alignment is addressed by extending Kotlarski's deconvolution formula to general dimensions and signals with vanishing Fourier transforms.