Bayesian Models for Registration of Functional Data

Jacopo Gardella; Rossella Carone; Simone Ciardulli; Nicola Francescon; Matteo Freddi; Elisa Garlanda; Alessandro Casa; Alessia Pini

doi:10.1007/978-3-031-64431-3_59

Bayesian Models for Registration of Functional Data

Jacopo Gardella, Rossella Carone, Simone Ciardulli, Nicola Francescon, Matteo Freddi, Elisa Garlanda, Alessandro Casa, Alessia Pini

Risultato della ricerca: Contributo in libro › Contributo a convegno

Abstract

Studies involving functional data frequently require curve registration, i.e. the alignment of salient features in the temporal domain, as a preliminary step before the application of inferential techniques. Through this procedure, phase variability becomes negligible, thus allowing to focus solely on amplitude variability. This work introduces a Bayesian model for curve alignment and applies it to a biomechanical dataset with three groups of patients.

Lingua originale	English
Titolo della pubblicazione ospite	Methodological and Applied Statistics and Demography III
Pagine	354-359
Numero di pagine	6
DOI	https://doi.org/10.1007/978-3-031-64431-3_59
Stato di pubblicazione	Pubblicato - 2025
Evento	SIS 2024 - Bari Durata: 17 giu 2024 → 20 giu 2024

Convegno

Convegno	SIS 2024
Città	Bari
Periodo	17/6/24 → 20/6/24

Keywords

Functional data, Bayesian warping, B-splines, Markov chain Monte Carlo

Accesso al documento

10.1007/978-3-031-64431-3_59

Altri file e collegamenti

Link a IRIS PubliCatt

Cita questo

@inproceedings{3eaf6f2ee713489f82e324628546461a,

title = "Bayesian Models for Registration of Functional Data",

abstract = "Studies involving functional data frequently require curve registration, i.e. the alignment of salient features in the temporal domain, as a preliminary step before the application of inferential techniques. Through this procedure, phase variability becomes negligible, thus allowing to focus solely on amplitude variability. This work introduces a Bayesian model for curve alignment and applies it to a biomechanical dataset with three groups of patients.",

keywords = "Functional data, Bayesian warping, B-splines, Markov chain Monte Carlo, Functional data, Bayesian warping, B-splines, Markov chain Monte Carlo",

author = "Jacopo Gardella and Rossella Carone and Simone Ciardulli and Nicola Francescon and Matteo Freddi and Elisa Garlanda and Alessandro Casa and Alessia Pini",

year = "2025",

doi = "10.1007/978-3-031-64431-3_59",

language = "English",

isbn = "9783031644306",

pages = "354--359",

booktitle = "Methodological and Applied Statistics and Demography III",

note = "SIS 2024 ; Conference date: 17-06-2024 Through 20-06-2024",

}

TY - GEN

T1 - Bayesian Models for Registration of Functional Data

AU - Gardella, Jacopo

AU - Carone, Rossella

AU - Ciardulli, Simone

AU - Francescon, Nicola

AU - Freddi, Matteo

AU - Garlanda, Elisa

AU - Casa, Alessandro

AU - Pini, Alessia

PY - 2025

Y1 - 2025

N2 - Studies involving functional data frequently require curve registration, i.e. the alignment of salient features in the temporal domain, as a preliminary step before the application of inferential techniques. Through this procedure, phase variability becomes negligible, thus allowing to focus solely on amplitude variability. This work introduces a Bayesian model for curve alignment and applies it to a biomechanical dataset with three groups of patients.

AB - Studies involving functional data frequently require curve registration, i.e. the alignment of salient features in the temporal domain, as a preliminary step before the application of inferential techniques. Through this procedure, phase variability becomes negligible, thus allowing to focus solely on amplitude variability. This work introduces a Bayesian model for curve alignment and applies it to a biomechanical dataset with three groups of patients.

KW - Functional data, Bayesian warping, B-splines, Markov chain Monte Carlo

UR - http://hdl.handle.net/10807/313061

U2 - 10.1007/978-3-031-64431-3_59

DO - 10.1007/978-3-031-64431-3_59

M3 - Conference contribution

SN - 9783031644306

SP - 354

EP - 359

BT - Methodological and Applied Statistics and Demography III

T2 - SIS 2024

Y2 - 17 June 2024 through 20 June 2024

ER -

Bayesian Models for Registration of Functional Data

Abstract

Convegno

Keywords

Accesso al documento

Altri file e collegamenti

Fingerprint

Cita questo