use short-circuit ops (|| and &&) as opposed to (| and &) to avoid warnings in...

use short-circuit ops (|| and &&) as opposed to (| and &) to avoid warnings in Octave (and save time)

matlab/AIM/SPExact_shift.m

@@ -34,7 +34,7 @@ left   = 1:qcols;
 right  = qcols+1:qcols+neq;
 zerorows = find( sum(abs( hs(:,right)' ))==0 );
 
-while( any(zerorows) & iq <= qrows )
+while( any(zerorows) && iq <= qrows )
    nz = length(zerorows);
    q(iq+1:iq+nz,:) = hs(zerorows,left);
    hs(zerorows,:)   = SPShiftright(hs(zerorows,:),neq);

matlab/AIM/SPNumeric_shift.m

@@ -35,7 +35,7 @@ right    = qcols+1:qcols+neq;
 [Q,R,E]  = qr( h(:,right) );
 zerorows = find( abs(diag(R)) <= condn );
 
-while( any(zerorows) & iq <= qrows )
+while( any(zerorows) && iq <= qrows )
    h=sparse(h);
    Q=sparse(Q);
    h = Q'*h;

matlab/CutSample.m

@@ -14,7 +14,7 @@ function CutSample(M_, options_, estim_params_)
 % SPECIAL REQUIREMENTS
 %    none
 
-% Copyright (C) 2005-2009 Dynare Team
+% Copyright (C) 2005-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -60,7 +60,7 @@ if (TotalNumberOfMhFiles-1)-(FirstMhFile+1)+1 > 0
                         record.MhDraws(end,3) ];
 elseif TotalNumberOfMhFiles == 1
     record.KeepedDraws.Distribution = [];
-elseif TotalNumberOfMhFiles == 2 & FirstMhFile > 1
+elseif TotalNumberOfMhFiles == 2 && FirstMhFile > 1
     record.KeepedDraws.Distribution = [MAX_nruns-FirstLine+1 ; record.MhDraws(end,3)];  
 end
 save([DirectoryName '/' M_.fname '_mh_history.mat'],'record');

matlab/DsgeLikelihood.m

@@ -47,14 +47,14 @@ nobs            = size(options_.varobs,1);
 %------------------------------------------------------------------------------
 % 1. Get the structural parameters & define penalties
 %------------------------------------------------------------------------------
-if options_.mode_compute ~= 1 & any(xparam1 < bayestopt_.lb)
+if options_.mode_compute ~= 1 && any(xparam1 < bayestopt_.lb)
     k = find(xparam1 < bayestopt_.lb);
     fval = bayestopt_.penalty+sum((bayestopt_.lb(k)-xparam1(k)).^2);
     cost_flag = 0;
     info = 41;
     return;
 end
-if options_.mode_compute ~= 1 & any(xparam1 > bayestopt_.ub)
+if options_.mode_compute ~= 1 && any(xparam1 > bayestopt_.ub)
     k = find(xparam1 > bayestopt_.ub);
     fval = bayestopt_.penalty+sum((xparam1(k)-bayestopt_.ub(k)).^2);
     cost_flag = 0;

matlab/DsgeVarLikelihood.m

@@ -59,7 +59,7 @@ mXX = evalin('base', 'mXX');
 fval = [];
 cost_flag = 1;
 
-if options_.mode_compute ~= 1 & any(xparam1 < bayestopt_.lb)
+if options_.mode_compute ~= 1 && any(xparam1 < bayestopt_.lb)
     k = find(xparam1 < bayestopt_.lb);
     fval = bayestopt_.penalty+sum((bayestopt_.lb(k)-xparam1(k)).^2);
     cost_flag = 0;
@@ -67,7 +67,7 @@ if options_.mode_compute ~= 1 & any(xparam1 < bayestopt_.lb)
     return;
 end
 
-if options_.mode_compute ~= 1 & any(xparam1 > bayestopt_.ub)
+if options_.mode_compute ~= 1 && any(xparam1 > bayestopt_.ub)
     k = find(xparam1 > bayestopt_.ub);
     fval = bayestopt_.penalty+sum((xparam1(k)-bayestopt_.ub(k)).^2);
     cost_flag = 0;

matlab/bvar_toolbox.m

@@ -42,7 +42,7 @@ function [ny, nx, posterior, prior, forecast_data] = bvar_toolbox(nlags)
 %    - bvar_prior_{tau,decay,lambda,mu,omega,flat,train}
 
 % Copyright (C) 2003-2007 Christopher Sims
-% Copyright (C) 2007-2009 Dynare Team
+% Copyright (C) 2007-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -87,7 +87,7 @@ end
 idx = options_.first_obs+options_.presample-train-nlags:options_.first_obs+options_.nobs-1;
 
 % Prepare dataset
-if options_.loglinear & ~options_.logdata
+if options_.loglinear && ~options_.logdata
     dataset = log(dataset);
 end
 if options_.prefilter
@@ -106,7 +106,7 @@ mu = options_.bvar_prior_mu;
 flat = options_.bvar_prior_flat;
 
 ny = size(dataset, 2);
-if options_.prefilter | options_.noconstant
+if options_.prefilter || options_.noconstant
     nx = 0;
 else
     nx = 1;
@@ -204,7 +204,7 @@ else
     breaks = [];
     lbreak = 0;
 end
-if ~isempty(vprior) & vprior.w>0
+if ~isempty(vprior) && vprior.w>0
     ydum2 = zeros(lags+1,nv,nv);
     xdum2 = zeros(lags+1,nx,nv);
     ydum2(end,:,:) = diag(vprior.sig);
@@ -286,7 +286,7 @@ y = ydata(smpl,:);
 % Everything now set up with input data for y=Xb+e 
 
 % Add persistence dummies
-if lambda ~= 0 | mu > 0
+if lambda ~= 0 || mu > 0
     ybar = mean(ydata(1:lags,:),1);
     if ~nox
         xbar = mean(xdata(1:lags,:),1);

matlab/check.m

@@ -11,7 +11,7 @@ function [result,info] = check
 % SPECIAL REQUIREMENTS
 %    none
 
-% Copyright (C) 2001-2010 Dynare Team
+% Copyright (C) 2001-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -33,7 +33,7 @@ global M_ options_ oo_
 
 temp_options = options_;
 tempex = oo_.exo_simul;
-if ~options_.initval_file & M_.exo_nbr > 1
+if ~options_.initval_file && M_.exo_nbr > 1
     oo_.exo_simul = ones(M_.maximum_lead+M_.maximum_lag+1,1)*oo_.exo_steady_state';
 end
 
@@ -47,7 +47,7 @@ end
 
 oo_.dr = dr;
 
-if info(1) ~= 0 & info(1) ~= 3 & info(1) ~= 4
+if info(1) ~= 0 && info(1) ~= 3 && info(1) ~= 4
     print_info(info, options_.noprint);
 end  
 
@@ -76,7 +76,7 @@ if options_.noprint == 0
     disp(sprintf('\nThere are %d eigenvalue(s) larger than 1 in modulus ', n_explod));
     disp(sprintf('for %d forward-looking variable(s)',nyf));
     disp(' ')
-    if dr.rank == nyf & nyf == n_explod
+    if dr.rank == nyf && nyf == n_explod
         disp('The rank condition is verified.')
     else
         disp('The rank conditions ISN''T verified!')

matlab/check_model.m

 function check_model()
 
-% Copyright (C) 2005-2009 Dynare Team
+% Copyright (C) 2005-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -29,7 +29,7 @@ if xlen > 1
             ' current period. Use additional endogenous variables']) ;
 end
 
-if (M_.exo_det_nbr > 0) & (M_.maximum_lag > 1 | M_.maximum_lead > 1)
+if (M_.exo_det_nbr > 0) && (M_.maximum_lag > 1 || M_.maximum_lead > 1)
     error(['Exogenous deterministic variables are currently only allowed in' ...
            ' models with leads and lags on only one period'])
 end

matlab/csminit.m

@@ -20,7 +20,7 @@ function [fhat,xhat,fcount,retcode] = csminit(fcn,x0,f0,g0,badg,H0,varargin)
 % http://sims.princeton.edu/yftp/optimize/mfiles/csminit.m
 
 % Copyright (C) 1993-2007 Christopher Sims
-% Copyright (C) 2008-2009 Dynare Team
+% Copyright (C) 2008-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -59,7 +59,7 @@ fhat=f0;
 g = g0;
 gnorm = norm(g);
 %
-if (gnorm < 1.e-12) & ~badg % put ~badg 8/4/94
+if (gnorm < 1.e-12) && ~badg % put ~badg 8/4/94
     retcode =1;
     dxnorm=0;
     % gradient convergence
@@ -138,14 +138,14 @@ else
         fcount=fcount+1;
         shrinkSignal = (~badg & (f0-f < max([-THETA*dfhat*lambda 0]))) | (badg & (f0-f) < 0) ;
         growSignal = ~badg & ( (lambda > 0)  &  (f0-f > -(1-THETA)*dfhat*lambda) );
-        if  shrinkSignal  &   ( (lambda>lambdaPeak) | (lambda<0) )
-            if (lambda>0) & ((~shrink) | (lambda/factor <= lambdaPeak))
+        if  shrinkSignal  &&   ( (lambda>lambdaPeak) || (lambda<0) )
+            if (lambda>0) && ((~shrink) || (lambda/factor <= lambdaPeak))
                 shrink=1;
                 factor=factor^.6;
                 while lambda/factor <= lambdaPeak
                     factor=factor^.6;
                 end
-                %if (abs(lambda)*(factor-1)*dxnorm < MINDX) | (abs(lambda)*(factor-1) < MINLAMB)
+                %if (abs(lambda)*(factor-1)*dxnorm < MINDX) || (abs(lambda)*(factor-1) < MINLAMB)
                 if abs(factor-1)<MINDFAC
                     if abs(lambda)<4
                         retcode=2;
@@ -155,12 +155,12 @@ else
                     done=1;
                 end
             end
-            if (lambda<lambdaMax) & (lambda>lambdaPeak)
+            if (lambda<lambdaMax) && (lambda>lambdaPeak)
                 lambdaMax=lambda;
             end
             lambda=lambda/factor;
             if abs(lambda) < MINLAMB
-                if (lambda > 0) & (f0 <= fhat)
+                if (lambda > 0) && (f0 <= fhat)
                     % try going against gradient, which may be inaccurate
                     lambda = -lambda*factor^6
                 else
@@ -172,11 +172,11 @@ else
                     done = 1;
                 end
             end
-        elseif  (growSignal & lambda>0) |  (shrinkSignal & ((lambda <= lambdaPeak) & (lambda>0)))
+        elseif  (growSignal && lambda>0) ||  (shrinkSignal && ((lambda <= lambdaPeak) && (lambda>0)))
             if shrink
                 shrink=0;
                 factor = factor^.6;
-                %if ( abs(lambda)*(factor-1)*dxnorm< MINDX ) | ( abs(lambda)*(factor-1)< MINLAMB)
+                %if ( abs(lambda)*(factor-1)*dxnorm< MINDX ) || ( abs(lambda)*(factor-1)< MINLAMB)
                 if abs(factor-1)<MINDFAC
                     if abs(lambda)<4
                         retcode=4;
@@ -186,7 +186,7 @@ else
                     done=1;
                 end
             end
-            if ( f<fPeak ) & (lambda>0)
+            if ( f<fPeak ) && (lambda>0)
                 fPeak=f;
                 lambdaPeak=lambda;
                 if lambdaMax<=lambdaPeak

matlab/csminwel1.m

@@ -23,7 +23,7 @@ function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel1(fcn,x0,H0,grad,crit,nit,m
 % http://sims.princeton.edu/yftp/optimize/mfiles/csminwel.m
 
 % Copyright (C) 1993-2007 Christopher Sims
-% Copyright (C) 2006-2010 Dynare Team
+% Copyright (C) 2006-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -105,7 +105,7 @@ while ~done
     % itct=itct+1;
     fcount = fcount+fc;
     % erased on 8/4/94
-    % if (retcode == 1) | (abs(f1-f) < crit)
+    % if (retcode == 1) || (abs(f1-f) < crit)
     %    done=1;
     % end
     % if itct > nit
@@ -113,7 +113,7 @@ while ~done
     %    retcode = -retcode;
     % end
     if retcode1 ~= 1
-        if retcode1==2 | retcode1==4
+        if retcode1==2 || retcode1==4
             wall1=1; badg1=1;
         else
             if NumGrad
@@ -134,7 +134,7 @@ while ~done
             %ARGLIST
             %save g1 g1 x1 f1 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13;
         end
-        if wall1 % & (~done) by Jinill
+        if wall1 % && (~done) by Jinill
                  % Bad gradient or back and forth on step length.  Possibly at
                  % cliff edge.  Try perturbing search direction.
                  %
@@ -147,7 +147,7 @@ while ~done
             %     P5,P6,P7,P8,P9,P10,P11,P12,P13);
             fcount = fcount+fc; % put by Jinill
             if  f2 < f
-                if retcode2==2 | retcode2==4
+                if retcode2==2 || retcode2==4
                     wall2=1; badg2=1;
                 else
                     if NumGrad
@@ -182,7 +182,7 @@ while ~done
                         %         P4,P5,P6,P7,P8,...
                         %      P9,P10,P11,P12,P13);
                         fcount = fcount+fc; % put by Jinill
-                        if retcode3==2 | retcode3==4
+                        if retcode3==2 || retcode3==4
                             wall3=1; badg3=1;
                         else
                             if NumGrad
@@ -218,13 +218,13 @@ while ~done
         f2=f;f3=f;f1=f;retcode2=retcode1;retcode3=retcode1;
     end
     %how to pick gh and xh
-    if f3 < f - crit & badg3==0 & f3 < f2 & f3 < f1
+    if f3 < f - crit && badg3==0 && f3 < f2 && f3 < f1
         ih=3;
         fh=f3;xh=x3;gh=g3;badgh=badg3;retcodeh=retcode3;
-    elseif f2 < f - crit & badg2==0 & f2 < f1
+    elseif f2 < f - crit && badg2==0 && f2 < f1
         ih=2;
         fh=f2;xh=x2;gh=g2;badgh=badg2;retcodeh=retcode2;
-    elseif f1 < f - crit & badg1==0
+    elseif f1 < f - crit && badg1==0
         ih=1;
         fh=f1;xh=x1;gh=g1;badgh=badg1;retcodeh=retcode1;
     else
@@ -271,7 +271,7 @@ while ~done
     %gh
     %badgh
     stuck = (abs(fh-f) < crit);
-    if (~badg)&(~badgh)&(~stuck)
+    if (~badg) && (~badgh) && (~stuck)
         H = bfgsi(H,gh-g,xh-x);
     end
     if Verbose
@@ -293,7 +293,7 @@ while ~done
         disp('smallest step still improving too slow, reversed gradient')
     elseif rc == 5
         disp('largest step still improving too fast')
-    elseif (rc == 4) | (rc==2)
+    elseif (rc == 4) || (rc==2)
         disp('back and forth on step length never finished')
     elseif rc == 3
         disp('smallest step still improving too slow')

matlab/csolve.m

@@ -22,7 +22,7 @@ function [x,rc] = csolve(FUN,x,gradfun,crit,itmax,varargin)
 % http://sims.princeton.edu/yftp/optimize/mfiles/csolve.m
 
 % Copyright (C) 1993-2007 Christopher Sims
-% Copyright (C) 2007 Dynare Team
+% Copyright (C) 2007-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -66,7 +66,7 @@ af00=af0;
 itct=0;
 while ~done
     %   disp([af00-af0 crit*max(1,af0)])
-    if itct>3 & af00-af0<crit*max(1,af0) & rem(itct,2)==1
+    if itct>3 && af00-af0<crit*max(1,af0) && rem(itct,2)==1
         randomize=1;
     else
         if ~analyticg
@@ -117,14 +117,14 @@ while ~done
             lambdamin=lambda;
             xmin=x+dx;
         end
-        if ((lambda >0) & (af0-af < alpha*lambda*af0)) | ((lambda<0) & (af0-af < 0) )
+        if ((lambda >0) && (af0-af < alpha*lambda*af0)) || ((lambda<0) && (af0-af < 0) )
             if ~shrink
                 factor=factor^.6;
                 shrink=1;
             end
             if abs(lambda*(1-factor))*dxSize > .1*delta;
                 lambda = factor*lambda;
-            elseif (lambda > 0) & (factor==.6) %i.e., we've only been shrinking
+            elseif (lambda > 0) && (factor==.6) %i.e., we've only been shrinking
                 lambda=-.3;
             else %
                 subDone=1;
@@ -138,7 +138,7 @@ while ~done
                     rc=3;
                 end
             end
-        elseif (lambda >0) & (af-af0 > (1-alpha)*lambda*af0)
+        elseif (lambda >0) && (af-af0 > (1-alpha)*lambda*af0)
             if shrink
                 factor=factor^.6;
                 shrink=0;

matlab/draw_prior_density.m

@@ -113,7 +113,7 @@ end
 k = [1:length(dens)];
 if pshape(indx) ~= 5 
     [junk,k1] = max(dens);
-    if k1 == 1 | k1 == length(dens)
+    if k1 == 1 || k1 == length(dens)
         k = find(dens < 10);
     end
 end

matlab/dyn_ramsey_dynamic_.m

@@ -213,7 +213,7 @@ k = 1:size(J,2);
 
 for i=1:n
     if sum(abs(J(:,i))) < 1e-8
-        if m(i) < n1 | m(i) > n2
+        if m(i) < n1 || m(i) > n2
             k(i) = 0;
             m(i) = 0;
         end

matlab/dynare_estimation.m

@@ -11,7 +11,7 @@ function dynare_estimation(var_list,varargin)
 % SPECIAL REQUIREMENTS
 %   none
 
-% Copyright (C) 2003-2010 Dynare Team
+% Copyright (C) 2003-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -62,13 +62,13 @@ else
     dynare_estimation_1(var_list,varargin{:});
 end
 
-if nnobs > 1 & horizon > 0
+if nnobs > 1 && horizon > 0
     mh_replic = options_.mh_replic;
     rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
     gend = options_.nobs;
     rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
     % Take the log of the variables if needed
-    if options_.loglinear & ~options_.logdata   % and if the data are not in logs, then...
+    if options_.loglinear && ~options_.logdata   % and if the data are not in logs, then...
         rawdata = log(rawdata);  
     end
 

matlab/dynare_estimation_1.m

@@ -77,10 +77,10 @@ if options_.prefilter == 1
 end
 
 %% Set options related to filtered variables.
-if options_.filtered_vars ~= 0 & isempty(options_.filter_step_ahead), 
+if options_.filtered_vars ~= 0 && isempty(options_.filter_step_ahead), 
     options_.filter_step_ahead = 1;
 end
-if options_.filtered_vars ~= 0 & options_.filter_step_ahead == 0,
+if options_.filtered_vars ~= 0 && options_.filter_step_ahead == 0,
     options_.filter_step_ahead = 1;
 end
 if options_.filter_step_ahead ~= 0
@@ -120,7 +120,7 @@ if ~isempty(estim_params_)
     end
     % Test if initial values of the estimated parameters are all between
     % the prior lower and upper bounds.
-    if any(xparam1 < bounds(:,1)) | any(xparam1 > bounds(:,2))
+    if any(xparam1 < bounds(:,1)) || any(xparam1 > bounds(:,2))
         find(xparam1 < bounds(:,1))
         find(xparam1 > bounds(:,2))
         error('Initial parameter values are outside parameter bounds')
@@ -684,7 +684,7 @@ if ~options_.mh_posterior_mode_estimation
     end
 end
 
-if options_.mode_check == 1 & ~options_.mh_posterior_mode_estimation
+if options_.mode_check == 1 && ~options_.mh_posterior_mode_estimation
     mode_check(xparam1,0,hh,gend,data,lb,ub,data_index,number_of_observations,no_more_missing_observations);
 end
 
@@ -703,7 +703,7 @@ else
 end
 
 
-if any(bayestopt_.pshape > 0) & ~options_.mh_posterior_mode_estimation
+if any(bayestopt_.pshape > 0) && ~options_.mh_posterior_mode_estimation
     disp(' ')
     disp('RESULTS FROM POSTERIOR MAXIMIZATION')
     tstath = zeros(nx,1);
@@ -815,7 +815,7 @@ if any(bayestopt_.pshape > 0) & ~options_.mh_posterior_mode_estimation
     disp(' ')
     disp(sprintf('Log data density [Laplace approximation] is %f.',md_Laplace))
     disp(' ')
-elseif ~any(bayestopt_.pshape > 0) & options_.mh_posterior_mode_estimation
+elseif ~any(bayestopt_.pshape > 0) && options_.mh_posterior_mode_estimation
     disp(' ')
     disp('RESULTS FROM MAXIMUM LIKELIHOOD')
     tstath = zeros(nx,1);
@@ -900,7 +900,7 @@ end
 
 OutputDirectoryName = CheckPath('Output');
 
-if any(bayestopt_.pshape > 0) & options_.TeX %% Bayesian estimation (posterior mode) Latex output
+if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior mode) Latex output
     if np
         filename = [OutputDirectoryName '/' M_.fname '_Posterior_Mode_1.TeX'];
         fidTeX = fopen(filename,'w');
@@ -1083,21 +1083,21 @@ if np > 0
     save([M_.fname '_params.mat'],'pindx');
 end
 
-if (any(bayestopt_.pshape  >0 ) & options_.mh_replic) | ...
-        (any(bayestopt_.pshape >0 ) & options_.load_mh_file)  %% not ML estimation
+if (any(bayestopt_.pshape  >0 ) && options_.mh_replic) || ...
+        (any(bayestopt_.pshape >0 ) && options_.load_mh_file)  %% not ML estimation
     bounds = prior_bounds(bayestopt_);
     bounds(:,1)=max(bounds(:,1),lb);
     bounds(:,2)=min(bounds(:,2),ub);
     bayestopt_.lb = bounds(:,1);
     bayestopt_.ub = bounds(:,2);
-    if any(xparam1 < bounds(:,1)) | any(xparam1 > bounds(:,2))
+    if any(xparam1 < bounds(:,1)) || any(xparam1 > bounds(:,2))
         find(xparam1 < bounds(:,1))
         find(xparam1 > bounds(:,2))
         error('Mode values are outside prior bounds. Reduce prior_trunc.')
     end
     % runs MCMC
     if options_.mh_replic
-        if options_.load_mh_file & options_.use_mh_covariance_matrix
+        if options_.load_mh_file && options_.use_mh_covariance_matrix
             invhess = compute_mh_covariance_matrix;
         end
         if options_.dsge_var
@@ -1111,7 +1111,7 @@ if (any(bayestopt_.pshape  >0 ) & options_.mh_replic) | ...
         CutSample(M_, options_, estim_params_);
         return
     else
-        if ~options_.nodiagnostic & options_.mh_replic > 1000 & options_.mh_nblck > 1
+        if ~options_.nodiagnostic && options_.mh_replic > 1000 && options_.mh_nblck > 1
             McMCDiagnostics(options_, estim_params_, M_);
         end
         %% Here i discard first half of the draws:
@@ -1131,7 +1131,7 @@ if (any(bayestopt_.pshape  >0 ) & options_.mh_replic) | ...
         if options_.moments_varendo
             oo_ = compute_moments_varendo('posterior',options_,M_,oo_,var_list_);
         end
-        if options_.smoother | ~isempty(options_.filter_step_ahead) | options_.forecast
+        if options_.smoother || ~isempty(options_.filter_step_ahead) || options_.forecast
             prior_posterior_statistics('posterior',data,gend,data_index,missing_value);
         end
         xparam = get_posterior_parameters('mean');
@@ -1139,9 +1139,9 @@ if (any(bayestopt_.pshape  >0 ) & options_.mh_replic) | ...
     end
 end
 
-if (~((any(bayestopt_.pshape > 0) & options_.mh_replic) | (any(bayestopt_.pshape ...
-                                                      > 0) & options_.load_mh_file)) ...
-    | ~options_.smoother ) & M_.endo_nbr^2*gend < 1e7 & options_.partial_information == 0  % to be fixed   
+if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape ...
+                                                      > 0) && options_.load_mh_file)) ...
+    || ~options_.smoother ) && M_.endo_nbr^2*gend < 1e7 && options_.partial_information == 0  % to be fixed   
     %% ML estimation, or posterior mode without metropolis-hastings or metropolis without bayesian smooth variable
     [atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp] = DsgeSmoother(xparam1,gend,data,data_index,missing_value);
     oo_.Smoother.SteadyState = ys;
@@ -1713,7 +1713,7 @@ if (~((any(bayestopt_.pshape > 0) & options_.mh_replic) | (any(bayestopt_.pshape
     end
 end
 
-if options_.forecast > 0 & options_.mh_replic == 0 & ~options_.load_mh_file 
+if options_.forecast > 0 && options_.mh_replic == 0 && ~options_.load_mh_file 
     forecast(var_list_,'smoother');
 end
 

matlab/initial_estimation_checks.m

@@ -75,7 +75,7 @@ if options_.steadystate_flag
     % Check if the steady state obtained from the _steadystate file is a 
     % steady state.
     check1 = 0;
-    if isfield(options_,'unit_root_vars') & options_.diffuse_filter == 0
+    if isfield(options_,'unit_root_vars') && options_.diffuse_filter == 0
         if isempty(options_.unit_root_vars)
             if ~options_.bytecode
                 check1 = max(abs(feval([M_.fname '_static'],...
@@ -101,7 +101,7 @@ if info(1) > 0
     print_info(info, options_.noprint)
 end
 
-if any(abs(oo_.steady_state(bayestopt_.mfys))>1e-9) & (options_.prefilter==1) 
+if any(abs(oo_.steady_state(bayestopt_.mfys))>1e-9) && (options_.prefilter==1) 
     disp(['You are trying to estimate a model with a non zero steady state for the observed endogenous'])
     disp(['variables using demeaned data!'])
     error('You should change something in your mod file...')

matlab/kalman/likelihood/kalman_filter.m

@@ -25,7 +25,7 @@ function [LIK, lik] = kalman_filter(T,R,Q,H,P,Y,start,mf,kalman_tol,riccati_tol)
 % NOTES
 %   The vector "lik" is used to evaluate the jacobian of the likelihood.
 
-% Copyright (C) 2004-2010 Dynare Team
+% Copyright (C) 2004-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -55,7 +55,7 @@ oldK = Inf;
 notsteady   = 1;                                % Steady state flag.
 F_singular  = 1;
 
-while notsteady & t<smpl
+while notsteady && t<smpl
     t  = t+1;
     v  = Y(:,t)-a(mf);
     F  = P(mf,mf) + H;

matlab/make_ex_.m

@@ -12,7 +12,7 @@ function make_ex_
 % SPECIAL REQUIREMENTS
 %  
 
-% Copyright (C) 1996-2009 Dynare Team
+% Copyright (C) 1996-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -36,7 +36,7 @@ options_ = set_default_option(options_,'periods',0);
 if isempty(oo_.exo_steady_state)
     oo_.exo_steady_state = zeros(M_.exo_nbr,1);
 end
-if M_.exo_det_nbr > 1 & isempty(oo_.exo_det_steady_state)
+if M_.exo_det_nbr > 1 && isempty(oo_.exo_det_steady_state)
     oo_.exo_det_steady_state = zeros(M_.exo_det_nbr,1);
 end
 if isempty(oo_.exo_simul)

matlab/marginal_density.m

@@ -15,7 +15,7 @@ function [marginal,oo_] = marginal_density(M_, options_, estim_params_, oo_)
 % SPECIAL REQUIREMENTS
 %    none
 
-% Copyright (C) 2005-2009 Dynare Team
+% Copyright (C) 2005-2011 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -94,7 +94,7 @@ while check_coverage
         marginal(linee,:) = [p, lpost_mode-log(tmp/((TotalNumberOfMhDraws-TODROP)*nblck))];
         warning(warning_old_state);
     end