Wavelets in Functional Data Analysis / / by Pedro A. Morettin, Aluísio Pinheiro, Brani Vidakovic

• Autore: Morettin Pedro A
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
• Edizione: 1st ed. 2017.
• Descrizione fisica: 1 online resource (VIII, 106 p. 44 illus., 25 illus. in color.)
• Disciplina: 515.7
• Soggetto topico: Functional analysis; Statistics; Mathematical models; Functional Analysis; Statistical Theory and Methods; Mathematical Modeling and Industrial Mathematics
• Persona (resp. second.): PinheiroAluísio; VidakovicBrani
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Preface -- Introduction Examples of Functional Data -- Wavelets -- Wavelet Shrinkage -- Wavelet-based Andrews Plots -- Functional ANOVA -- Further topics.
• Sommario/riassunto: Wavelet-based procedures are key in many areas of statistics, applied mathematics, engineering, and science. This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data. Starting with the Haar wavelet, the authors explore myriad families of wavelets and how they can be used. High-dimensional data visualization (using Andrews' plots), wavelet shrinkage (a simple, yet powerful, procedure for nonparametric models) and a selection of estimation and testing techniques (including a discussion on Stein’s Paradox) make this a highly valuable resource for graduate students and experienced researchers alike.
• Titolo autorizzato: Wavelets in Functional Data Analysis
• ISBN: 3-319-59623-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910254298003321
• Lo trovi qui: Univ. Federico II
• Serie: SpringerBriefs in Mathematics, . 2191-8201