📄 asfig09.m
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% asfig09 -- Asymptopia Figure 09: Comparison to Good-Gaskins Smoother
%
% Here we illustrate the application of wavelet thresholding to Poisson
% Counts data. The Good-Gaskins 1980 scattering data are transformed by the Anscombe
% variance-stabilizing transformation for poisson data, which are
% then processed exactly as if the data obeyed the white noise model.
%
% Note that for these data, the wavelet result is very closely comparable
% to the result that Good and Gaskins obtained by using computationally
% much more challenging methods.
%
%
global t xh y rootgood
load scatter
y = 2.*sqrt(scatter + .375);
t =(-135):10:(-135+255*10);
QMF_Filter = MakeONFilter('Coiflet',3);
[xh,wcoef] = WaveShrink(y,'Visu',5,QMF_Filter);
%
%clf;
load goodfit;
rootgood = 2*sqrt(goodfit+.375);
versaplot(311,t,xh,[],'9 (a) Wavelet Shrinkage (-); Good&Gaskins (..)',[],1)
versaplot(311,t,rootgood,'-.',[],[],0)
versaplot(312,t,xh-rootgood,[],'9 (b) Wavelet-Good&Gaskins' ,[],[])
versaplot(325,t,xh,[],'9 (c) Closeup ',[500 900 20 60],1);
versaplot(325,t,rootgood,'-.',[],[],1);
versaplot(325,t,y,'.',[],[],0);
versaplot(326,t,xh,[],'9 (d) Closeup ',[1000 1400 20 40],1);
versaplot(326,t,rootgood,'-.',[],[],1);
versaplot(326,t,y,'.',[],[],0);
%
% Prepared for the paper Wavelet Shrinkage: Asymptopia?
% Copyright (c) 1994 David L. Donoho and Iain M. Johnstone
%
% Revision History
% 09/29/99 MRD declared variables global
% 10/1/05 AM changeing the name of the variable QMF to QMF_Filter
%
%% Part of Wavelab Version 850% Built Tue Jan 3 13:20:41 EST 2006% This is Copyrighted Material% For Copying permissions see COPYING.m% Comments? e-mail wavelab@stat.stanford.edu
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