4 papers
Detecting relevant differences in the covariance operators of functional time series -- a sup-norm approach
Holger Dette, Kevin Kokot
In this paper we propose statistical inference tools for the covariance operators of functional time series in the two sample and change point problem. In contrast to most of the l…
Efficient tests for bio-equivalence in functional data
Holger Dette, Kevin Kokot
We study the problem of testing the equivalence of functional parameters (such as the mean or variance function) in the two sample functional data problem. In contrast to previous…
Testing relevant hypotheses in functional time series via self-normalization
Holger Dette, Kevin Kokot, Stanislav Volgushev
In this paper we develop methodology for testing relevant hypotheses about functional time series in a tuning-free way. Instead of testing for exact equality, for example for the e…
Functional data analysis in the Banach space of continuous functions
Holger Dette, Kevin Kokot, Alexander Aue
Functional data analysis is typically conducted within the -Hilbert space framework. There is by now a fully developed statistical toolbox allowing for the principled applicat…