Permutation methods for multi-aspect local inference on functional data

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

Permutation methods for multi-aspect local inference on functional data

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Cladag 2017 Meeting of the Classification and Data Analysis Group Book of Short Papers
Publisher	Universitas Studiorum S.r.l. Casa Editrice
Pages	1-4
Number of pages	4
ISBN (Print)	978-88-99459-71-0
Publication status	Published - 2017

Keywords

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

Cite this

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title = "Permutation methods for multi-aspect local inference on functional data",

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.",

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T1 - Permutation methods for multi-aspect local inference on functional data

AU - Pini, Alessia

AU - Spreafico, L.

AU - Vantini, S.

AU - Vietti, A.

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Articulatory Phonetics

KW - Derivatives

KW - Functional Data Analysis

KW - Inference

KW - Interval-Wise Error Rate

KW - Articulatory Phonetics

KW - Derivatives

KW - Functional Data Analysis

KW - Inference

KW - Interval-Wise Error Rate

UR - https://publicatt.unicatt.it/handle/10807/119850

M3 - Conference contribution

SN - 978-88-99459-71-0

SP - 1

EP - 4

BT - Cladag 2017 Meeting of the Classification and Data Analysis Group Book of Short Papers

PB - Universitas Studiorum S.r.l. Casa Editrice

ER -

Permutation methods for multi-aspect local inference on functional data

Abstract

Keywords

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