Nonparametric Inference for Spatiotemporal Data Based on Local Null Hypothesis Testing for Functional Data

Alessia Pini*, Simone Vantini

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in libroChapter

Abstract

We discuss the interval-wise testing procedure: an inferential technique that can be applied to spatiotemporal data in order to test differences between groups of functional data defined either in time or space. IWT is based on the definition of an unadjusted and an adjusted p -value function that can be used to locally test a functional null hypothesis over the domain of functional data. When applied to spatiotemporal data, this technique can identify intervals of time or regions of space imputable for the rejection of a functional null hypothesis. The technique is illustrated and applied to a benchmark data set of Canadian temperatures, to test differences between different regions.
Lingua originaleEnglish
Titolo della pubblicazione ospiteGeostatistical Functional Data Analysis
EditorJ. Mateu, R. Giraldo
Pagine242-259
Numero di pagine18
DOI
Stato di pubblicazionePubblicato - 2022

Serie di pubblicazioni

NomeWILEY SERIES IN PROBABILITY

Keywords

  • Canadian climate
  • interval wise testing
  • nonparametric inference
  • null hypothesis significance testing

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