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Wavelet-based estimation of 1/f-type signal parameters: confidence intervals using the bootstrap

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1 Author(s)
A. M. Sabatini ; ARTSLab., Scuola Superiore Sant' Anna, Pisa, Italy

We propose to construct confidence intervals of parameters of 1/f-type signals using a nonparametric wavelet-based bootstrap method. Bootstrap-based confidence intervals of maximum likelihood parameter estimates are compared to the confidence intervals derived from the Cramer-Rao lower bound (CRLB). For moderately large data sample sizes, the bootstrap approach achieves the nominal coverage and may perform better than the CRLB-based parametric approach

Published in:

IEEE Transactions on Signal Processing  (Volume:47 ,  Issue: 12 )