var z dw dx dy dc1 dc2 w x y; varexo e_w e_x e_y e_z; parameters rho_w rho_x rho_y rho_z a1 a2 a3 b c; model(linear); dw = rho_w*dw(-1)+a1*(dc1(-1))+e_w; dx = rho_x*dx(-1)+a2*(dc1(-1))+e_x; dy = rho_y*dy(-1)+a3*(dc2(-1))+e_y; z = rho_z*z(-1)+dw-dx+e_z; dc1 = dc1(-1)+dx-b*dy-c*dw; dc2 = dc2(-1)+dx-b*dy; w = w(-1) + dw; x = x(-1) + dx; y = y(-1) + dy; end; estimated_params; rho_w, normal_pdf, 0.5,0.2; rho_x, normal_pdf, 0.5,0.2; rho_y, normal_pdf, 0.5,0.2; rho_z, normal_pdf, 0.8,0.2; a1, normal_pdf, 0.1,0.2; a2, normal_pdf, -0.1,0.2; a3, normal_pdf, 0.1,0.2; b , normal_pdf, 1,0.2; c , normal_pdf, 1,0.2; stderr e_w, uniform_pdf,,, 0.01, 0.1; stderr e_x, uniform_pdf,,, 0.01, 0.1; stderr e_y, uniform_pdf,,, 0.01, 0.1; stderr e_z, inv_gamma_pdf,0.01, inf; end; varobs w x y; estimation(datafile=data,first_obs=1000,nobs=200,mh_replic=0,mode_compute=0,mode_file='algo3/Output/algo3_mode',diffuse_filter,kalman_algo=4,filtered_vars,smoothed_state_uncertainty); //checking smoother consistency X = oo_.SmoothedVariables; S = [X.z X.dw X.dx X.dy X.dc1 X.dc2 X.w X.x X.y]; X = oo_.SmoothedShocks; E = [X.e_w X.e_x X.e_y X.e_z]; A = oo_.dr.ghx; B = oo_.dr.ghu; err = zeros(M_.endo_nbr,200); for t=2:200; err(:,t) = S(t,:)'-A*S(t-1,:)'-B*E(t,:)'; end; if max(max(abs(err))) > 1e-10; error('Test fails'); end; d=load('data'); dat = [d.w d.x d.y]; if max(max(abs(dat(1000:1199,:)-S(:,[7:9])))) > 1e-10; error('Test fails'); end; o1 = load(['algo3' filesep 'Output' filesep 'algo3_results.mat']); obj_endo={'SmoothedVariables'; 'FilteredVariables'; 'UpdatedVariables'}; obj_exo = {'SmoothedShocks';}; nobj_endo = size(obj_endo,1); nobj_exo = size(obj_exo,1); for i=1:nobj_endo; err_endo = zeros(eval(['size(oo_.' obj_endo{i} '.' M_.endo_names{1} ',1);']),M_.endo_nbr); for j=1:M_.endo_nbr; var1 = eval(['o1.oo_.' obj_endo{i} '.' M_.endo_names{j}]); var2 = eval(['oo_.' obj_endo{i} '.' M_.endo_names{j}]); err_endo(:,j) = var1-var2; end; if max(max(abs(err_endo))) > 1e-10; error('Test fails'); end; end; err_exo = zeros(200,M_.exo_nbr,nobj_exo); for i=1:nobj_exo; err_exo = zeros(size(eval(['oo_.' obj_exo{i} '.' M_.exo_names{1}]),1),M_.exo_nbr); for j=1:M_.exo_nbr; var1 = eval(['o1.oo_.' obj_exo{i} '.' M_.exo_names{j}]); var2 = eval(['oo_.' obj_exo{i} '.' M_.exo_names{j}]); err_exo(:,j,i) = var1 - var2; end; if max(max(abs(err_exo))) > 1e-10; error('Test fails'); end; end;