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_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_results');
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;

