Title :
Wavelet-based estimation of 1/f-type signal parameters: confidence intervals using the bootstrap
Author :
Sabatini, Angelo M.
Author_Institution :
ARTSLab., Scuola Superiore Sant´´ Anna, Pisa, Italy
fDate :
12/1/1999 12:00:00 AM
Abstract :
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
Keywords :
maximum likelihood estimation; nonparametric statistics; parameter estimation; signal processing; statistical analysis; stochastic processes; time series; wavelet transforms; 1/f-type signal parameters; Cramer-Rao lower bound; bootstrap; confidence intervals; maximum likelihood parameter estimates; moderately large data sample sizes; nonparametric wavelet-based bootstrap method; statistical signal processing; stochastic processes; wavelet-based estimation; Discrete wavelet transforms; Estimation theory; Maximum likelihood detection; Maximum likelihood estimation; Parameter estimation; Signal analysis; Signal processing; Signal processing algorithms; Stochastic processes; Wavelet analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
