Overview
- Brings together results in wavelet functional data analysis that to date were only available in papers
- The only book to present functional data analysis from a wavelet point of view in a general framework
- Offers numerous sample coded applications for use with MATLAB
- Includes chapters in state-of-the-art topics like visualization of functional analysis via wavelets, optimal estimation and testing methods
Part of the book series: SpringerBriefs in Mathematics (BRIEFSMATH)
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Table of contents (6 chapters)
Keywords
About this book
Reviews
Authors and Affiliations
About the authors
Aluísio Pinheiro holds a B.S. and M.S. in Statistics from National School of Statistical Sciences (ENCE), Brazil, and University of Campinas, respectively. He also has a Ph.D. in Statistics from the University of North Carolina at Chapel Hill, USA. He is currently affiliated to the University of Campinas. His main research areas are nonparametric statistics, estimation and asymptotics, particularly wavelets and U-statistics. In 2012 he was awarded the P. K. Sen Distinguished Visiting Professorship of Biostatistics at the University of North Carolina.
Brani Vidakovic holds a B.S. in Mathematics and a M.S. in Probability from Belgrade University, Serbia, and a Ph.D. in Statistics from Purdue University, USA (1992). He is currently affiliated to Georgia Tech and Emory University, both in the USA. His main research areas are Bayesian modeling, wavelet statistics and multi-scale data analysis. He was the recipient of the 1992 Burr's award for best Ph.D. student at Purdue University. He is an associate editor of several leading statistical journals.
Bibliographic Information
Book Title: Wavelets in Functional Data Analysis
Authors: Pedro A. Morettin, Aluísio Pinheiro, Brani Vidakovic
Series Title: SpringerBriefs in Mathematics
DOI: https://doi.org/10.1007/978-3-319-59623-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2017
Softcover ISBN: 978-3-319-59622-8Published: 23 November 2017
eBook ISBN: 978-3-319-59623-5Published: 07 November 2017
Series ISSN: 2191-8198
Series E-ISSN: 2191-8201
Edition Number: 1
Number of Pages: VIII, 106
Number of Illustrations: 19 b/w illustrations, 25 illustrations in colour
Topics: Functional Analysis, Statistical Theory and Methods, Mathematical Modeling and Industrial Mathematics