Wavelets In Functional Data Analysis (springerbriefs In Mathematics)
by Brani Vidakovic /
2017 / English / PDF
6.8 MB Download
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.
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.
