False discovery rate for functional data

@article{Olsen2019FalseDR,
  title={False discovery rate for functional data},
  author={Niels Lundtorp Olsen and Alessia Pini and Simone Vantini},
  journal={TEST},
  year={2019},
  volume={30},
  pages={784-809}
}
Since Benjamini and Hochberg introduced false discovery rate (FDR) in their seminal paper, this has become a very popular approach to the multiple comparisons problem. An increasingly popular topic within functional data analysis is local inference, i.e. the continuous statistical testing of a null hypothesis along the domain. The principal issue in this topic is the infinite amount of tested hypotheses, which can be seen as an extreme case of the multiple comparisons problem. In this paper, we… 
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3 Citations

3 Citations

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