Functional data mining with multiscale statistical procedures

Functional data mining with multiscale statistical procedures

Hurst exponent and variance are two quantities that often characterize real-life, highfrequency observations. We develop the method for simultaneous estimation of a timechanging Hurst exponent H(t) and constant scale (variance) parameter C in a multifractional Brownian motion model in the presence o...

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Bibliographic Details
Main Author: Lee, Kichun
Published: Georgia Institute of Technology 2010
Subjects:
Multifractality
Wavelets
Hurst exponent
Fractional Brownian motion
Multifractional Brownian motion
Semi-supervised learning
Data mining
Correlation (Statistics)
Wavelets (Mathematics)
Supervised learning (Machine learning)
Machine learning
Online Access:http://hdl.handle.net/1853/34716

Internet

http://hdl.handle.net/1853/34716

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