diff --git a/matlab/DsgeLikelihood.m b/matlab/DsgeLikelihood.m
index 40f4e223b..3e08aaa90 100644
--- a/matlab/DsgeLikelihood.m
+++ b/matlab/DsgeLikelihood.m
@@ -21,7 +21,7 @@ function [fval,cost_flag,ys,trend_coeff,info] = DsgeLikelihood(xparam1,gend,data
 % SPECIAL REQUIREMENTS
 %
 
-% Copyright (C) 2004-2009 Dynare Team
+% Copyright (C) 2004-2009, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -314,7 +314,11 @@ if (kalman_algo==4)% Univariate Diffuse Kalman Filter
                                                     no_more_missing_observations);
     end
 end
-if imag(LIK) ~= 0
+if isnan(LIK)
+    cost_flag = 0;
+    return
+end
+if imag(LIK)~=0
     likelihood = bayestopt_.penalty;
 else
     likelihood = LIK;
diff --git a/matlab/kalman/likelihood/diffuse_kalman_filter.m b/matlab/kalman/likelihood/diffuse_kalman_filter.m
index e6464cbe3..16623486e 100644
--- a/matlab/kalman/likelihood/diffuse_kalman_filter.m
+++ b/matlab/kalman/likelihood/diffuse_kalman_filter.m
@@ -23,7 +23,7 @@ function [LIK, lik] = diffuse_kalman_filter(T,R,Q,H,Pinf,Pstar,Y,start,Z,kalman_
 %   Models", S.J. Koopman and J. Durbin (2003, in Journal of Time Series 
 %   Analysis, vol. 24(1), pp. 85-98). 
 
-% Copyright (C) 2004-2008 Dynare Team
+% Copyright (C) 2004-2008, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -95,7 +95,9 @@ while rank(Pinf,kalman_tol) && (t<smpl)
 end
 
 if t == smpl
-    error(['There isn''t enough information to estimate the initial conditions of the nonstationary variables']);                   
+    warning(['There isn''t enough information to estimate the initial conditions of the nonstationary variables']);                   
+    LIK = NaN;
+    return
 end
 
 F_singular = 1;
@@ -125,7 +127,9 @@ while notsteady && (t<smpl)
 end
 
 if F_singular == 1
-    error(['The variance of the forecast error remains singular until the end of the sample'])
+    warning(['The variance of the forecast error remains singular until the end of the sample'])
+    LIK = NaN;
+    return
 end
 
 if t < smpl
diff --git a/matlab/kalman/likelihood/missing_observations_diffuse_kalman_filter.m b/matlab/kalman/likelihood/missing_observations_diffuse_kalman_filter.m
index ae578d3a2..f9ebb7d2b 100644
--- a/matlab/kalman/likelihood/missing_observations_diffuse_kalman_filter.m
+++ b/matlab/kalman/likelihood/missing_observations_diffuse_kalman_filter.m
@@ -27,7 +27,7 @@ function [LIK, lik] = missing_observations_diffuse_kalman_filter(T,R,Q,H,Pinf,Ps
 %   Models", S.J. Koopman and J. Durbin (2003, in Journal of Time Series 
 %   Analysis, vol. 24(1), pp. 85-98). 
 
-% Copyright (C) 2004-2008 Dynare Team
+% Copyright (C) 2004-2008, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -111,7 +111,9 @@ while rank(Pinf,kalman_tol) && (t<smpl)
 end
 
 if t == smpl
-    error(['There isn''t enough information to estimate the initial conditions of the nonstationary variables']);                   
+    warning(['There isn''t enough information to estimate the initial conditions of the nonstationary variables']);                   
+    LIK = NaN;
+    return
 end
 
 F_singular = 1;
@@ -155,7 +157,9 @@ while notsteady && (t<smpl)
 end
 
 if F_singular == 1
-    error(['The variance of the forecast error remains singular until the end of the sample'])
+    warning(['The variance of the forecast error remains singular until the end of the sample'])
+    LIK = NaN;
+    return
 end
 
 if t < smpl
diff --git a/matlab/kalman/likelihood/univariate_diffuse_kalman_filter.m b/matlab/kalman/likelihood/univariate_diffuse_kalman_filter.m
index f42cb8ff4..925b2bbeb 100644
--- a/matlab/kalman/likelihood/univariate_diffuse_kalman_filter.m
+++ b/matlab/kalman/likelihood/univariate_diffuse_kalman_filter.m
@@ -28,7 +28,7 @@ function [LIK, lik] = univariate_diffuse_kalman_filter(T,R,Q,H,Pinf,Pstar,Y,star
 % NOTES
 %   The vector "lik" is used to evaluate the jacobian of the likelihood.
 
-% Copyright (C) 2004-2009 Dynare Team
+% Copyright (C) 2004-2009, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -100,6 +100,8 @@ end
 
 if (t==smpl)
     error(['univariate_diffuse_kalman_filter:: There isn''t enough information to estimate the initial conditions of the nonstationary variables']);
+    LIK = NaN;
+    return
 end
 
 while notsteady && (t<smpl)
diff --git a/matlab/kalman/likelihood/univariate_diffuse_kalman_filter_corr.m b/matlab/kalman/likelihood/univariate_diffuse_kalman_filter_corr.m
index 62b0cdac7..0370b89ca 100644
--- a/matlab/kalman/likelihood/univariate_diffuse_kalman_filter_corr.m
+++ b/matlab/kalman/likelihood/univariate_diffuse_kalman_filter_corr.m
@@ -29,7 +29,7 @@ function [LIK, lik] = univariate_diffuse_kalman_filter_corr(T,R,Q,H,Pinf,Pstar,Y
 % NOTES
 %   The vector "lik" is used to evaluate the jacobian of the likelihood.
 
-% Copyright (C) 2004-2008 Dynare Team
+% Copyright (C) 2004-2008, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -148,7 +148,9 @@ while newRank && (t<smpl)
 end
 
 if (t==smpl)
-    error(['univariate_diffuse_kalman_filter:: There isn''t enough information to estimate the initial conditions of the nonstationary variables']);
+    warning(['univariate_diffuse_kalman_filter:: There isn''t enough information to estimate the initial conditions of the nonstationary variables']);
+    LIK = NaN;
+    return
 end
 
 while notsteady && (t<smpl)
diff --git a/matlab/kalman/likelihood/univariate_kalman_filter.m b/matlab/kalman/likelihood/univariate_kalman_filter.m
index 6a536294d..6b23ef792 100644
--- a/matlab/kalman/likelihood/univariate_kalman_filter.m
+++ b/matlab/kalman/likelihood/univariate_kalman_filter.m
@@ -28,7 +28,7 @@ function [LIK, lik] = univariate_kalman_filter(T,R,Q,H,P,Y,start,mf,kalman_tol,r
 % NOTES
 %   The vector "lik" is used to evaluate the jacobian of the likelihood.
 
-% Copyright (C) 2004-2008 Dynare Team
+% Copyright (C) 2004-2008, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %
diff --git a/matlab/mode_check.m b/matlab/mode_check.m
index c6d92c482..f2936ef68 100644
--- a/matlab/mode_check.m
+++ b/matlab/mode_check.m
@@ -18,7 +18,7 @@ function mode_check(x,fval,hessian,gend,data,lb,ub,data_index,number_of_observat
 % SPECIAL REQUIREMENTS
 %    none
 
-% Copyright (C) 2003-2009 Dynare Team
+% Copyright (C) 2003-2009, 2010 Dynare Team
 %
 % This file is part of Dynare.
 %