diff --git a/matlab/distributions/mode_and_variance_to_mean.m b/matlab/distributions/mode_and_variance_to_mean.m
index 89b604fcb..c632ef35c 100644
--- a/matlab/distributions/mode_and_variance_to_mean.m
+++ b/matlab/distributions/mode_and_variance_to_mean.m
@@ -4,17 +4,18 @@ function [mu, parameters] = mode_and_variance_to_mean(m,s2,distribution,lower_bo
 %  INPUTS 
 %    m                [double]    scalar, mode of the distribution.
 %    s2               [double]    scalar, variance of the distribution.
-%    distribution     [string]    name of the distribution ("gamma","inv-gamma-2","inv-gamma-1","beta")    
+%    distribution     [integer]   scalar for the distribution shape 
+%                                    1 gamma
+%                                    2 inv-gamma-2
+%                                    3 inv-gamma-1
+%                                    4 beta    
 %    lower_bound      [double]    scalar, lower bound of the random variable support (optional).
 %    upper_bound      [double]    scalar, upper bound of the random variable support (optional).
 %    
 %  OUTPUT 
 %    mu               [double]    scalar, mean of the distribution.
 %    parameters       [double]    2*1 vector, parameters of the distribution.
-%    info             [integer]   scalar. If info=1 we have a multiplicity of solutions.     
-%                                         If info=2 we have no solution.
-%  ALGORITHM 
-%    Described in "Prior Distribution in Dynare".
+%    
 
 % Copyright (C) 2009 Dynare Team
 %
@@ -34,82 +35,72 @@ function [mu, parameters] = mode_and_variance_to_mean(m,s2,distribution,lower_bo
 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
 
     % Check input aruments. 
-    if ~(nargin==3 || nargin==5 || nargin==4)
+    if ~(nargin==3 || nargin==5 || nargin==4 )
         error('mode_and_variance_to mean:: 3 or 5 input arguments are needed!')
     end
-    if ~ischar(distribution)
-        error(['mode_and_variance_to_mean:: Third argument must be a string!'])
-    end
     
     % Set defaults bounds.
     if nargin==3
         switch distribution
-          case 'gamma'
+          case 1
             lower_bound = 0;
             upper_bound = Inf;
-          case 'inv-gamma-1'
+          case 3
             lower_bound = 0;
             upper_bound = Inf;
-          case 'inv-gamma-2'
+          case 2
             lower_bound = 0;
             upper_bound = Inf;
-          case 'beta'
+          case 4
             lower_bound = 0;
             upper_bound = 1;
           otherwise
-            disp(['mode_and_variance_to mean:: ' distribution ' is an unknown distribution...'])
-            disp('                              distribution is equal to ''beta'', ''gamma'',')
-            disp('                              ''inv-gamma-1'' or ''inv-gamma-2'' ')
-            error()
+            error('Unknown distribution!')
         end
     end
     if nargin==4
         switch distribution
-          case 'gamma'
+          case 1
             upper_bound = Inf;
-          case 'inv-gamma-1'
+          case 3
             upper_bound = Inf;
-          case 'inv-gamma-2'
+          case 2
             upper_bound = Inf;
-          case 'beta'
+          case 4
             upper_bound = 1;
           otherwise
-            disp(['mode_and_variance_to mean:: ' distribution ' is an unknown distribution...'])
-            disp('                              distribution is equal to ''beta'', ''gamma'',')
-            disp('                              ''inv-gamma-1'' or ''inv-gamma-2'' ')
-            error()
+            error('Unknown distribution!')
         end
     end
     
     
-    if strcmpi(distribution,'gamma')
+    if (distribution==1)% Gamma distribution
         if m<lower_bound
-            error('mode_and_variance_to_mean:: The mode has to be greater than the lower bound!')
+            error('The mode has to be greater than the lower bound!')
         end
         if (m-lower_bound)<1e-12
-            error('mode_and_variance_to_mean:: The gamma distribution should be specified with the mean and variance.')
+            error('The gamma distribution should be specified with the mean and variance.')
         end        
         m = m - lower_bound ;
-        tmp = 1-sqrt(4*s2/(m*m));
-        alpha = 1 - 2/tmp;
-        beta  = -.5*m*tmp;
+        beta  = -.5*m*(1-sqrt(1+4*s2/(m*m))) ;
+        alpha = (m+beta)/beta ;
         parameters(1) = alpha;
         parameters(2) = beta;
         mu = alpha*beta + lower_bound ;
         return
     end
     
-    if strcmpi(distribution,'inv-gamma-2')
+    if (distribution==2)% Inverse Gamma - 2 distribution
         if m<lower_bound+2*eps
-            error('mode_and_variance_to_mean:: The mode has to be greater than the lower bound!')
+            error('The mode has to be greater than the lower bound!')
         end
         m = m - lower_bound ;
         if isinf(s2)
-           nu = 2;
-           s  = 4*m;
+           nu = 4;
+           s  = 2*m;
         else
-            delta = 2*m*m/s2;
-            poly = [ 1 , -6 , 12-delta , -8-2*delta ];
+            delta = 2*(m*m/s2);
+            poly = [ 1 , -(8+delta) , 20-4*delta , -(16+4*delta) ];
             all_roots  = roots(poly);
             real_roots = all_roots(find(abs(imag(all_roots))<2*eps));
             nu = real_roots(find(real_roots>2));
@@ -121,23 +112,22 @@ function [mu, parameters] = mode_and_variance_to_mean(m,s2,distribution,lower_bo
         return
     end
     
-    if strcmpi(distribution,'inv-gamma-1')
+    if (distribution==3)% Inverted Gamma 1 distribution
         if m<lower_bound+2*eps
-            error('mode_and_variance_to_mean:: The mode has to be greater than the lower bound!')
+            error('The mode has to be greater than the lower bound!')
         end
         m = m - lower_bound ;
         if isinf(s2)
            nu = 2;
            s  = 1/(m*m);
         else
-            [mu, parameters] = mode_and_variance_to_mean(m,s2,'inv-gamma-2');
+            [mu, parameters] = mode_and_variance_to_mean(m,s2,2);
             nu = sqrt(parameters(1));
             nu2 = 2*nu;
             nu1 = 2;
-            tmp = s2*m*m;
-            err = tmp - (nu-1)/(nu-2) + .5*(nu-1)*(gamma((nu-1)/2)/gamma(nu/2))^2;
+            err = s2*(m*m) - (nu-1)/(nu-2) + .5*(nu-1)*(gamma((nu-1)/2)/gamma(nu/2))^2;
             while abs(nu2-nu1) > 1e-12
-                if err > 0
+                if err < 0
                     nu1 = nu;
                     if nu < nu2
                         nu = nu2;
@@ -149,9 +139,9 @@ function [mu, parameters] = mode_and_variance_to_mean(m,s2,distribution,lower_bo
                     nu2 = nu;
                 end
                 nu =  (nu1+nu2)/2;
-                err = tmp - (nu-1)/(nu-2) + .5*(nu-1)*(gamma((nu-1)/2)/gamma(nu/2))^2;
+                err = s2*(m*m) - (nu-1)/(nu-2) + .5*(nu-1)*(gamma((nu-1)/2)/gamma(nu/2))^2;
             end
-            s = (nu-1)/m^2 ;
+            s = (nu-1)/(m*m) ;
         end
         parameters(1) = nu;
         parameters(2) = s;
@@ -159,35 +149,35 @@ function [mu, parameters] = mode_and_variance_to_mean(m,s2,distribution,lower_bo
         return
     end
             
-    if strcmpi(distribution,'beta')
+    if (distribution==4)% Beta distribution
         if m<lower_bound
-            error('mode_and_variance_to_mean:: The mode has to be greater than the lower bound!')
+            error('The mode has to be greater than the lower bound!')
         end
         if m>upper_bound
-            error('mode_and_variance_to_mean:: The mode has to be less than the upper bound!')
+            error('The mode has to be less than the upper bound!')
         end
         if (m-lower_bound)<1e-12
-            error('mode_and_variance_to_mean:: The beta distribution should be specified with the mean and variance.')
+            error('The beta distribution should be specified with the mean and variance.')
         end
         if (upper_bound-m)<1e-12
-            error('mode_and_variance_to_mean:: The beta distribution should be specified with the mean and variance.')
+            error('The beta distribution should be specified with the mean and variance.')
         end
         ll = upper_bound-lower_bound;
-        m  = (m-lower_bound)/ll ;
-        s2 = s2/(ll*ll) ;
+        m  = (m-lower_bound)/ll;
+        s2 = s2/(ll*ll);
+        delta = m^2/s2;
         poly = NaN(1,4);
-        poly(1) = 1/m^3;
-        poly(2) = (7*m*s2-3*s2+m^3-m^2)/(m^3*s2);
-        poly(3) = (16*m^2*s2-14*m*s2+3*s2-2*m^3+m^2)/(m^3*s2);
-        poly(4) = 12*m^3-16*m^2-7*m-1;
+        poly(1) = 1;
+        poly(2) = 7*m-(1-m)*delta-3;
+        poly(3) = 16*m^2-14*m+3-2*m*delta+delta;
+        poly(4) = 12*m^3-16*m^2+7*m-1;
         all_roots = roots(poly);
         real_roots = all_roots(find(abs(imag(all_roots))<2*eps));
         idx = find(real_roots>1);
         if length(idx)>1
-            error('mode_and_variance_to_mean:: Multiplicity of solutions for the beta distribution specification.')
+            error('Multiplicity of solutions for the beta distribution specification.')
         elseif isempty(idx)
-            disp('mode_and_variance_to_mean:: No solution for the beta distribution specification.')
-            disp('                            You should reduce the variance.');
+            disp('No solution for the beta distribution specification. You should reduce the variance.')
             error();
         end
         alpha = real_roots(idx);