Permutation methods for multi-aspect local inference on functional data

Alessia Pini, L. Spreafico, S. Vantini, A. Vietti

Risultato della ricerca: Contributo in libroContributo a convegno

Abstract

We present in this talk a local non-parametric technique for making inference on multiple aspects of functional data simultaneously. The technique provides adjusted multi-aspect p-value functions that can be used to select intervals of the domain imputable for the rejection of a null hypothesis. We show the application of the proposed technique to the functional data analysis of a data set of tongue profiles recorded for a study on Tyrolean, a German dialect spoken in South Tyrol.
Lingua originaleEnglish
Titolo della pubblicazione ospiteCladag 2017 Meeting of the Classification and Data Analysis Group Book of Short Papers
Pagine1-4
Numero di pagine4
Stato di pubblicazionePubblicato - 2017
EventoCladag 2017 Meeting of the Classification and Data Analysis Group - Milano
Durata: 13 set 201715 set 2017

Convegno

ConvegnoCladag 2017 Meeting of the Classification and Data Analysis Group
CittàMilano
Periodo13/9/1715/9/17

Keywords

  • Functional Data Analysis, Inference, Interval-Wise Error Rate, Derivatives, Articulatory Phonetics

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