Removed unnecessary parts of the code.
 Call resol instead of dynare_resolve.  Removed definition of constant and trend which are not used in nonlinear filters.  Cosmetic changes.
...  ...  @@ 144,7 +144,7 @@ end 
%  
% Linearize the model around the deterministic sdteadystate and extract the matrices of the state equation (T and R).  
[T,R,SteadyState,info,Model,DynareOptions,DynareResults] = dynare_resolve(Model,DynareOptions,DynareResults,'restrict');  
[dr, info, Model, DynareOptions, DynareResults] = resol(0, Model, DynareOptions, DynareResults);  
if info(1)  
if info(1) == 3  info(1) == 4  info(1) == 5  info(1)==6 info(1) == 19  ...  
...  ...  @@ 166,34 +166,14 @@ end 
% Define a vector of indices for the observed variables. Is this really usefull?...  
BayesInfo.mf = BayesInfo.mf1;  
% Define the deterministic linear trend of the measurement equation.  
if DynareOptions.noconstant  
constant = zeros(DynareDataset.vobs,1);  
else  
constant = SteadyState(BayesInfo.mfys);  
end  
% Define the deterministic linear trend of the measurement equation.  
if BayesInfo.with_trend  


[trend_addition, trend_coeff]=compute_trend_coefficients(Model,DynareOptions,DynareDataset.vobs,DynareDataset.nobs);  
trend = repmat(constant,1,DynareDataset.info.ntobs)+trend_addition;  
else  
trend = repmat(constant,1,DynareDataset.nobs);  
end  
% Get needed informations for kalman filter routines.  
start = DynareOptions.presample+1;  
np = size(T,1);  
mf = BayesInfo.mf;  
Y = transpose(DynareDataset.data);  
Y = transpose(DynareDataset.data);  
%  
% 3. Initial condition of the Kalman filter  
%  
% Get decision rules and transition equations.  
dr = DynareResults.dr;  
% Set persistent variables (first call).  
if isempty(init_flag)  
mf0 = BayesInfo.mf0;  
...  ...  @@ 270,7 +250,7 @@ DynareOptions.warning_for_steadystate = 1; 
% Adds prior if necessary  
%   
lnprior = priordens(xparam1(:),BayesInfo.pshape,BayesInfo.p6,BayesInfo.p7,BayesInfo.p3,BayesInfo.p4);  
fval = (likelihoodlnprior);  
fval = (likelihoodlnprior);  
if isnan(fval)  
fval = Inf;  
...  ...  @@ 280,7 +260,7 @@ if isnan(fval) 
return  
end  
if imag(fval)~=0  
if ~isreal(fval)  
fval = Inf;  
info(1) = 48;  
info(4) = 0.1;  
...  ...  @@ 288,7 +268,7 @@ if imag(fval)~=0 
return  
end  
if isinf(LIK)~=0  
if isinf(LIK)  
fval = Inf;  
info(1) = 50;  
info(4) = 0.1;  
...  ... 

mentioned in issue #1673

mentioned in issue #1690 (closed)