Efficient tests for bio-equivalence in functional data
Loading...
Date
2020
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
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 work, which reduces the functional problem to a multiple testing problem for the
equivalence of scalar data by comparing the functions at each point, our approach is based
on an estimate of a distance measuring the maximum deviation between the two functional
parameters. Equivalence is claimed if the estimate for the maximum deviation does not
exceed a given threshold. A bootstrap procedure is proposed to obtain quantiles for the
distribution of the test statistic and consistency of the corresponding test is proved in the
large sample scenario. As the methods proposed here avoid the use of the intersectionunion
principle they are less conservative and more powerful than the currently available
methodology.
Description
Table of contents
Keywords
equivalence tests, Banach space valued random variables, maximum deviation, bootstrap, two sample problems, functional data