umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Differential interval-wise testing for local inference in Sobolev spaces
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.ORCID iD: 0000-0001-9235-3062
2017 (English)In: Functional Statistics and Related Fields / [ed] G. Aneiros, E. Bongiorno, R. Cao, P. Vieu, Springer, 2017Chapter in book (Refereed)
Abstract [en]

We present a local non-parametric inferential technique - namely, the differential interval-wise testing, or D-IWT - able to test the distributional equality of two samples of functional data embedded in Sobolev spaces. D-IWT can impute differences between the two samples to specific parts of the domain and to specific orders of differentiation. The proposed technique is applied to the functional data analysis of a data set of tongue profiles.

Place, publisher, year, edition, pages
Springer, 2017.
Series
Contributions to Statistics
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-138839ISBN: 978-3-319-55846-2 (electronic)OAI: oai:DiVA.org:umu-138839DiVA: diva2:1137869
Available from: 2017-09-01 Created: 2017-09-01 Last updated: 2017-09-01

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Pini, Alessia
By organisation
Statistics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

Total: 17 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf