Wavelet-based bootstrapping of spatial patterns on a finite lattice
Computational Statistics & Data Analysis
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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