Reducing the bias of the wavelet estimate of spectral density

This paper is devoted to the development of methods of the bias reduction for a wavelet estimate of spectral density of a stationary discrete time random process. The method is based on an estimate for the upper boundary of the bias obtained limited spectral densities satisfying the Lipschitz condition. These results can be used for creating algorithms for the calculation of wavelet estimates of spectral densities with a given accuracy.