Autor(en): Dette, Holger
Kokot, Kevin
Titel: Efficient tests for bio-equivalence in functional data
Sprache (ISO): en
Zusammenfassung: 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.
Schlagwörter: equivalence tests
Banach space valued random variables
maximum deviation
bootstrap
two sample problems
functional data
Schlagwörter (RSWK): Funktionale Datenanalyse
URI: http://hdl.handle.net/2003/39097
http://dx.doi.org/10.17877/DE290R-21015
Erscheinungsdatum: 2020
Enthalten in den Sammlungen:Sonderforschungsbereich (SFB) 823

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
DP_1120_SFB823_Dette_Kokot.pdfDNB1.82 MBAdobe PDFÖffnen/Anzeigen


Diese Ressource ist urheberrechtlich geschützt.



Diese Ressource ist urheberrechtlich geschützt. rightsstatements.org