hartigansdipsigniftest.m

function		[dip, p_value, xlow,xup]=HartigansDipSignifTest(xpdf,sh,nboot)

%  function		[dip,p_value,xlow,xup]=HartigansDipSignifTest(xpdf,nboot)
%
% calculates Hartigan's DIP statistic and its significance for the empirical p.d.f  XPDF (vector of sample values)
% This routine calls the matlab routine 'HartigansDipTest' that actually calculates the DIP
% NBOOT is the user-supplied sample size of boot-strap
% Code by F. Mechler (27 August 2002)

% calculate the DIP statistic from the empirical pdf
[dip,xlow,xup, ifault, gcm, lcm, mn, mj]=hartigansdiptest(xpdf);
N=length(xpdf);

% calculate a bootstrap sample of size NBOOT of the dip statistic for a uniform pdf of sample size N (the same as empirical pdf)
boot_dip=[];
for i=1:nboot
    unifpdfboot=sort(unifrnd(0,1,1,N));
    %    sim_data=poissrnd(d.random(lns,1));
    %[c,l]=wavedec(sim_data(find(~isnan(sim_data))),15,'haar');
    %[eas,ed_sim]=wenergy(c,l);
    %sim_hist=ed_sim'/sum(ed_sim);
    %xr=samp_dist(sh,100);
   [unif_dip]=hartigansdiptest(unifpdfboot);
   boot_dip=[boot_dip; unif_dip];
end;
boot_dip=sort(boot_dip);
p_value=sum(dip<boot_dip)/nboot;

% % Plot Boot-strap sample and the DIP statistic of the empirical pdf
% figure(1); clf;
% [hy,hx]=hist(boot_dip); 
% bar(hx,hy,'k'); hold on;
% plot([dip dip],[0 max(hy)*1.1],'r:');