stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

in MCF analysis, separated marginal and cumulative (Smirnov) plots. 

This is the marginal function

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@712 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
ratto 2006-04-12 10:02:34 +00:00
parent 378523f736
commit ca3d913db7
1 changed files with 61 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

61
matlab/stab_map_marginal.m Normal file
View File

@ -0,0 +1,61 @@
function [proba, dproba] = stab_map_marginal(lpmat, ibehaviour, inonbehaviour, aname, ishock)
%function stab_map_1(lpmat, ibehaviour, inonbehaviour, aname, ishock)
%
% lpmat = Monte Carlo matrix
% ibehaviour = index of behavioural runs
% inonbehaviour = index of non-behavioural runs
% ishock = 1 estimated shocks included
% ishock = 0 estimated shocks excluded (default)
%
% Plots: dotted lines for BEHAVIOURAL
% solid lines for NON BEHAVIOURAL
% USES smirnov
global estim_params_ bayestopt_ M_ options_
if nargin<5,
ishock=0;
end
fname_ = M_.fname;
nshock = estim_params_.nvx;
nshock = nshock + estim_params_.nvn;
nshock = nshock + estim_params_.ncx;
nshock = nshock + estim_params_.ncn;
number_of_grid_points = 2^9; % 2^9 = 512 !... Must be a power of two.
bandwidth = 0; % Rule of thumb optimal bandwidth parameter.
kernel_function = 'gaussian'; % Gaussian kernel for Fast Fourrier Transform approximaton.
%kernel_function = 'uniform'; % Gaussian kernel for Fast Fourrier Transform approximaton.
if ishock,
npar = nshock + estim_params_.np;
else
npar = estim_params_.np;
end
for i=1:ceil(npar/12),
figure,
for j=1+12*(i-1):min(npar,12*i),
subplot(3,4,j-12*(i-1))
optimal_bandwidth = mh_optimal_bandwidth(lpmat(ibehaviour,j),length(ibehaviour),bandwidth,kernel_function);
[x1,f1] = kernel_density_estimate(lpmat(ibehaviour,j),number_of_grid_points,...
optimal_bandwidth,kernel_function);
plot(x1, f1,':k','linewidth',2)
optimal_bandwidth = mh_optimal_bandwidth(lpmat(inonbehaviour,j),length(inonbehaviour),bandwidth,kernel_function);
[x1,f1] = kernel_density_estimate(lpmat(inonbehaviour,j),number_of_grid_points,...
optimal_bandwidth,kernel_function);
hold on, plot(x1, f1,'k','linewidth',2)
%hist(lpmat(ibehaviour,j),30)
if ishock,
title(bayestopt_.name{j},'interpreter','none')
else
title(bayestopt_.name{j+nshock},'interpreter','none')
end
end
saveas(gcf,[fname_,'_',aname,'_',int2str(i)])
eval(['print -depsc2 ' fname_ '_' aname '_' int2str(i)]);
eval(['print -dpdf ' fname_ '_' aname '_' int2str(i)]);
if options_.nograph, close(gcf), end
end