Some new methods for wavelet density estimation.
David R.M. Herrick, Guy P. Nason and Bernard W. Silverman
This article proposes some non-linear, thresholded wavelet density estimators,
and investigates the practical problems involved in their implementation.
Our proposed thresholding method exploits the non-stationary variance structure
of the wavelet coefficients. One proposed method of estimating the variances
of the raw coefficients uses the scaling function coefficients. Since these are
available as a by-product of the discrete wavelet transform, no extra effort
is required to find them.
The performance of the methodology is assessed on a real dataset from a
forensic application and simulated data from a well known test function.