90 lines
3.2 KiB
Matlab
90 lines
3.2 KiB
Matlab
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function proba = stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, ishock)
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%function stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, ishock)
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%
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% lpmat = Monte Carlo matrix
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% ibehaviour = index of behavioural runs
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% inonbehaviour = index of non-behavioural runs
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% ishock = 1 estimated shocks included
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% ishock = 0 estimated shocks excluded (default)
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%
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% Plots: dotted lines for BEHAVIOURAL
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% solid lines for NON BEHAVIOURAL
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% USES smirnov
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global estim_params_ bayestopt_ M_
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if nargin<5,
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ishock=0;
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end
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fname_ = M_.fname;
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nshock = estim_params_.nvx;
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nshock = nshock + estim_params_.nvn;
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nshock = nshock + estim_params_.ncx;
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nshock = nshock + estim_params_.ncn;
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number_of_grid_points = 2^9; % 2^9 = 512 !... Must be a power of two.
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bandwidth = 0; % Rule of thumb optimal bandwidth parameter.
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kernel_function = 'gaussian'; % Gaussian kernel for Fast Fourrier Transform approximaton.
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%kernel_function = 'uniform'; % Gaussian kernel for Fast Fourrier Transform approximaton.
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if ishock,
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npar = nshock + estim_params_.np;
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else
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npar = estim_params_.np;
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end
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for i=1:ceil(npar/12),
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figure,
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for j=1+12*(i-1):min(npar,12*i),
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subplot(3,4,j-12*(i-1))
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optimal_bandwidth = mh_optimal_bandwidth(lpmat(ibehaviour,j),length(ibehaviour),bandwidth,kernel_function);
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[x1,f1] = kernel_density_estimate(lpmat(ibehaviour,j),number_of_grid_points,...
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optimal_bandwidth,kernel_function);
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plot(x1, f1,':k','linewidth',2)
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optimal_bandwidth = mh_optimal_bandwidth(lpmat(inonbehaviour,j),length(inonbehaviour),bandwidth,kernel_function);
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[x1,f1] = kernel_density_estimate(lpmat(inonbehaviour,j),number_of_grid_points,...
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optimal_bandwidth,kernel_function);
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hold on, plot(x1, f1,'k','linewidth',2)
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%hist(lpmat(ibehaviour,j),30)
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if ishock,
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title(bayestopt_.name{j},'interpreter','none')
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else
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title(bayestopt_.name{j+nshock},'interpreter','none')
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end
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end
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saveas(gcf,[fname_,'_',aname,'_',int2str(i)])
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end
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% Smirnov test for Blanchard;
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for i=1:ceil(npar/12),
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figure,
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for j=1+12*(i-1):min(npar,12*i),
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subplot(3,4,j-12*(i-1))
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if ~isempty(ibehaviour),
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h=cumplot(lpmat(ibehaviour,j));
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set(h,'color',[0 0 0], 'linestyle',':')
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end
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hold on,
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if ~isempty(inonbehaviour),
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h=cumplot(lpmat(inonbehaviour,j));
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set(h,'color',[0 0 0])
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end
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% if exist('kstest2')==2 & length(inonbehaviour)>0 & length(inonbehaviour)<Nsam,
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% [H,P,KSSTAT] = kstest2(lpmat(ibehaviour,j),lpmat(inonbehaviour,j));
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% title([bayestopt_.name{j+nshock},'. K-S prob ', num2str(P)])
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% else
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[H,P,KSSTAT] = smirnov(lpmat(ibehaviour,j),lpmat(inonbehaviour,j));
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if ishock,
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tittxt = bayestopt_.name{j};
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else
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tittxt = bayestopt_.name{j+nshock};
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end
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title([tittxt,'. K-S prob ', num2str(P)],'interpreter','none')
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proba(j)=P;
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% end
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end
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saveas(gcf,[fname_,'_',aname,'_SA_',int2str(i)])
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end
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