Fixed indentation.

externals/x13/installx13.m

@@ -17,7 +17,7 @@ function installx13()
 % You should have received a copy of the GNU General Public License
 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
 
-    
+
 if ~exist('x13.zip','file')
     if ( ~isoctave() && verLessThan('matlab', 'R2014b') )
         websave('x13.zip', 'http://www.dynare.org/x13/x13.zip');

externals/x13/uninstallx13.m

@@ -17,7 +17,7 @@ function uninstallx13()
 % You should have received a copy of the GNU General Public License
 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
 
-    
+
 if exist('x13.zip','file')
     delete('x13.zip')
 end

src/@arima/estimate.m

@@ -219,6 +219,3 @@ end
 %$
 %$ T = all(t);
 %@eof:1
-
-
-

src/@dseries/abs.m

@@ -2,10 +2,10 @@ function o = abs(o) % --*-- Unitary tests --*--
 
 % Apply the absolute value to all the variables in a dseries object (without in place modification).
 %
-% INPUTS 
+% INPUTS
 % - o [dseries]
 %
-% OUTPUTS 
+% OUTPUTS
 % - o [dseries]
 
 % Copyright (C) 2011-2017 Dynare Team
@@ -41,7 +41,7 @@ o.abs_;
 %$ catch
 %$     t(1) = false;
 %$ end
-%$ 
+%$
 %$ if t(1)
 %$      t(2) = dassert(o, q);
 %$      t(3) = dassert(p.data, ones(10, 2));
@@ -63,7 +63,7 @@ o.abs_;
 %$ catch
 %$     t(1) = false;
 %$ end
-%$ 
+%$
 %$ if t(1)
 %$      t(2) = dassert(length(p.name), 2);
 %$      t(3) = dassert(p.name{1},'abs(Variable_1)');

src/@dseries/abs_.m

@@ -2,10 +2,10 @@ function o = abs_(o) % --*-- Unitary tests --*--
 
 % Apply the absolute value to all the variables in a dseries object (in place modification).
 %
-% INPUTS 
+% INPUTS
 % - o [dseries]
 %
-% OUTPUTS 
+% OUTPUTS
 % - o [dseries]
 
 % Copyright (C) 2017 Dynare Team
@@ -70,7 +70,7 @@ o.data = abs(o.data);
 %$ catch
 %$     t(1) = false;
 %$ end
-%$ 
+%$
 %$ if t(1)
 %$      t(2) = dassert(length(o.name), 2);
 %$      t(3) = dassert(o.name{1},'abs(Variable_1)');

src/@dseries/align.m

 function [o, p] = align(o, p) % --*-- Unitary tests --*--
 
 % If necessay completes dseries object o and p so that they are defined on the same time range
-% (in place modification). 
-%    
-% INPUTS 
+% (in place modification).
+%
+% INPUTS
 % - o [dseries]
 % - p [dseries]
 %
-% OUTPUTS 
+% OUTPUTS
 % - o [dseries]
 % - p [dseries]
 

src/@dseries/align_.m

 function [o, p] = align_(o, p) % --*-- Unitary tests --*--
-    
+
 % If necessay completes dseries object o and p so that they are defined on the same time range
-% (in place modification). 
-%    
-% INPUTS 
+% (in place modification).
+%
+% INPUTS
 % - o [dseries]
 % - p [dseries]
 %
-% OUTPUTS 
+% OUTPUTS
 % - o [dseries]
 % - p [dseries]
 

src/@dseries/baxter_king_filter.m

 function o = baxter_king_filter(o, high_frequency, low_frequency, K) % --*-- Unitary tests --*--
 
 % Implementation of Baxter and King (1999) band pass filter for dseries objects. The code is adapted from
-% the one provided by Baxter and King. This filter isolates business cycle fluctuations with a period of length 
+% the one provided by Baxter and King. This filter isolates business cycle fluctuations with a period of length
 % ranging between high_frequency to low_frequency (quarters).
 %
-% INPUTS 
+% INPUTS
 %  - o                  dseries object.
 %  - high_frequency     positive scalar, period length (default value is 6).
 %  - low_frequency      positive scalar, period length (default value is 32).
 %  - K                  positive scalar integer, truncation parameter (default value is 12).
 %
-% OUTPUTS 
+% OUTPUTS
 %  - o                  dseries object.
 %
-% REMARKS 
-% This filter use a (symmetric) moving average smoother, so that K observations at the beginning and at the end of the 
+% REMARKS
+% This filter use a (symmetric) moving average smoother, so that K observations at the beginning and at the end of the
 % sample are lost in the computation of the filter.
 
 % Copyright (C) 2013-2017 Dynare Team
@@ -65,7 +65,7 @@ o.baxter_king_filter_(high_frequency, low_frequency, K);
 %$ % Create a dataset.
 %$ e = .2*randn(200,1);
 %$ u = randn(200,1);
-%$ stochastic_trend = cumsum(e); 
+%$ stochastic_trend = cumsum(e);
 %$ deterministic_trend = .1*transpose(1:200);
 %$ x = zeros(200,1);
 %$ for i=2:200

src/@dseries/baxter_king_filter_.m

 function o = baxter_king_filter_(o, high_frequency, low_frequency, K) % --*-- Unitary tests --*--
 
 % Implementation of Baxter and King (1999) band pass filter for dseries objects. The code is adapted from
-% the one provided by Baxter and King. This filter isolates business cycle fluctuations with a period of length 
+% the one provided by Baxter and King. This filter isolates business cycle fluctuations with a period of length
 % ranging between high_frequency to low_frequency (quarters).
 %
-% INPUTS 
+% INPUTS
 %  - o                  dseries object.
 %  - high_frequency     positive scalar, period length (default value is 6).
 %  - low_frequency      positive scalar, period length (default value is 32).
 %  - K                  positive scalar integer, truncation parameter (default value is 12).
 %
-% OUTPUTS 
+% OUTPUTS
 %  - o                  dseries object.
 %
-% REMARKS 
-% This filter use a (symmetric) moving average smoother, so that K observations at the beginning and at the end of the 
+% REMARKS
+% This filter use a (symmetric) moving average smoother, so that K observations at the beginning and at the end of the
 % sample are lost in the computation of the filter.
 
 % Copyright (C) 2013-2017 Dynare Team
@@ -55,7 +55,7 @@ if nargin<4 || isempty(K)
         end
     end
 end
-       
+
 % translate periods into frequencies.
 hf=2.0*pi/high_frequency;
 lf=2.0*pi/low_frequency;
@@ -86,7 +86,7 @@ tmp = zeros(size(o.data));
 
 % Filtering step.
 for t = K+1:nobs(o)-K
-    tmp(t,:)  = weights'*o.data(t-K:t+K,:);    
+    tmp(t,:)  = weights'*o.data(t-K:t+K,:);
 end
 
 % Update dseries object.
@@ -105,7 +105,7 @@ end
 %$ % Create a dataset.
 %$ e = .2*randn(200,1);
 %$ u = randn(200,1);
-%$ stochastic_trend = cumsum(e); 
+%$ stochastic_trend = cumsum(e);
 %$ deterministic_trend = .1*transpose(1:200);
 %$ x = zeros(200,1);
 %$ for i=2:200

src/@dseries/center.m

@@ -2,11 +2,11 @@ function o = center(o, geometric) % --*-- Unitary tests --*--
 
 % Centers dseries object o around its mean (arithmetic or geometric).
 %
-% INPUTS 
+% INPUTS
 %  - o             dseries object [mandatory].
 %  - geometric     logical [default is false], if true returns the geometric mean.
 %
-% OUTPUTS 
+% OUTPUTS
 %  - o             dseries object.
 
 % Copyright (C) 2016-2017 Dynare Team

src/@dseries/center_.m

@@ -2,11 +2,11 @@ function o = center_(o, geometric) % --*-- Unitary tests --*--
 
 % Centers dseries object o around its mean (arithmetic or geometric).
 %
-% INPUTS 
+% INPUTS
 %  - o             dseries object [mandatory].
 %  - geometric     logical [default is false], if true returns the geometric mean.
 %
-% OUTPUTS 
+% OUTPUTS
 %  - o             dseries object.
 
 % Copyright (C) 2016-2017 Dynare Team

src/@dseries/chain.m

@@ -2,14 +2,14 @@ function q = chain(o, p)  % --*-- Unitary tests --*--
 
 % Chains two dseries objects.
 %
-% INPUTS 
+% INPUTS
 % - o     [dseries]
 % - p     [dseries]
 %
-% OUTPUTS 
+% OUTPUTS
 % - q     [dseries]
 %
-% REMARKS 
+% REMARKS
 % The two dseries objects must have common frequency and the same number of variables. Also the
 % two samples must overlap.
 

src/@dseries/copy.m

@@ -27,7 +27,7 @@ p = dseries();
 p.data  = o.data;
 p.name  = o.name;
 p.tex   = o.tex;
-p.dates = o.dates; 
+p.dates = o.dates;
 
 %@test:1
 %$ % Define a dates object
@@ -42,7 +42,7 @@ p.dates = o.dates;
 %$ catch
 %$     t(1) = false;
 %$ end
-%$ 
+%$
 %$ if t(1)
 %$      o.log_();
 %$      t(2) = dassert(p, q);

src/@dseries/cumprod_.m

@@ -49,23 +49,23 @@ end
 
 switch nargin
   case 1
-      % Initialize the output.
-      o = varargin{1};
-      % Perform the cumulated sum
-      if isequal(idx, 1)
-          o.data = cumprod(o.data);
-      else
-          if common_first_period_witout_nan
-              o.data(idx:end,:) = cumprod(o.data(idx:end,:));
-          else
-              o.data = cumprodnan(o.data);
-          end
-      end
-      % Change the name of the variables
-      for i=1:vobs(o)
-          o.name(i) = {['cumprod(' o.name{i} ')']};
-          o.tex(i) = {['\prod_t ' o.tex{i}]};
-      end
+    % Initialize the output.
+    o = varargin{1};
+    % Perform the cumulated sum
+    if isequal(idx, 1)
+        o.data = cumprod(o.data);
+    else
+        if common_first_period_witout_nan
+            o.data(idx:end,:) = cumprod(o.data(idx:end,:));
+        else
+            o.data = cumprodnan(o.data);
+        end
+    end
+    % Change the name of the variables
+    for i=1:vobs(o)
+        o.name(i) = {['cumprod(' o.name{i} ')']};
+        o.tex(i) = {['\prod_t ' o.tex{i}]};
+    end
   case 2
     if isdseries(varargin{2})
         if ~isequal(vobs(varargin{1}), vobs(varargin{2}))

src/@dseries/cumsum.m

@@ -2,12 +2,12 @@ function o = cumsum(varargin) % --*-- Unitary tests --*--
 
 % Overloads matlab's cumsum function for dseries objects.
 %
-% INPUTS 
+% INPUTS
 % - o     dseries object [mandatory].
 % - d     dates object [optional]
 % - v     dseries object with one observation [optional]
 %
-% OUTPUTS 
+% OUTPUTS
 % - o     dseries object.
 
 % Copyright (C) 2013-2017 Dynare Team

src/@dseries/cumsum_.m

@@ -2,12 +2,12 @@ function o = cumsum_(varargin) % --*-- Unitary tests --*--
 
 % Overloads matlab's cumsum function for dseries objects.
 %
-% INPUTS 
+% INPUTS
 % - o     dseries object [mandatory].
 % - d     dates object [optional]
 % - v     dseries object with one observation [optional]
 %
-% OUTPUTS 
+% OUTPUTS
 % - o     dseries object.
 
 % Copyright (C) 2013-2017 Dynare Team
@@ -48,24 +48,24 @@ else
 end
 
 switch nargin
-    case 1
-      % Initialize the output.
-      o = varargin{1};
-      % Perform the cumulated sum
-      if isequal(idx, 1)
-          o.data = cumsum(o.data);
-      else
-          if common_first_period_witout_nan
-              o.data(idx:end,:) = cumsum(o.data(idx:end,:));
-          else
-              o.data = cumsumnan(o.data);
-          end
-      end
-      % Change the name of the variables
-      for i=1:vobs(o)
-          o.name(i) = {['cumsum(' o.name{i} ')']};
-          o.tex(i) = {['\sum_t ' o.tex{i}]};
-      end
+  case 1
+    % Initialize the output.
+    o = varargin{1};
+    % Perform the cumulated sum
+    if isequal(idx, 1)
+        o.data = cumsum(o.data);
+    else
+        if common_first_period_witout_nan
+            o.data(idx:end,:) = cumsum(o.data(idx:end,:));
+        else
+            o.data = cumsumnan(o.data);
+        end
+    end
+    % Change the name of the variables
+    for i=1:vobs(o)
+        o.name(i) = {['cumsum(' o.name{i} ')']};
+        o.tex(i) = {['\sum_t ' o.tex{i}]};
+    end
   case 2
     if isdseries(varargin{2})
         if ~isequal(vobs(varargin{1}), vobs(varargin{2}))

src/@dseries/detrend.m

@@ -2,11 +2,11 @@ function o = detrend(o, model) % --*-- Unitary tests --*--
 
 % Detrends a dseries object with a polynomial of order model.
 %
-% INPUTS 
-% - o       [dseries]   time series to be detrended. 
+% INPUTS
+% - o       [dseries]   time series to be detrended.
 % - model   [integer]   scalar, order of the fitted polynomial.
 %
-% OUTPUTS 
+% OUTPUTS
 % - o       [dseries]   detrended time series.
 
 % Copyright (C) 2014-2017 Dynare Team

src/@dseries/detrend_.m

@@ -2,11 +2,11 @@ function o = detrend_(o, model) % --*-- Unitary tests --*--
 
 % Detrends a dseries object with a polynomial of order model.
 %
-% INPUTS 
-% - o       [dseries]   time series to be detrended. 
+% INPUTS
+% - o       [dseries]   time series to be detrended.
 % - model   [integer]   scalar, order of the fitted polynomial.
 %
-% OUTPUTS 
+% OUTPUTS
 % - o       [dseries]   detrended time series.
 
 % Copyright (C) 2014-2017 Dynare Team

src/@dseries/disp.m

@@ -2,10 +2,10 @@ function disp(o)
 
 % Overloads disp method.
 %
-% INPUTS 
+% INPUTS
 % - o  [dseries]   Object to be displayed.
 %
-% OUTPUTS 
+% OUTPUTS
 % None
 
 % Copyright (C) 2011-2017 Dynare Team

src/@dseries/display.m

@@ -2,13 +2,13 @@ function display(o)
 
 % Overloads display method.
 %
-% INPUTS 
+% INPUTS
 % - o  [dseries]   Object to be displayed.
 %
-% OUTPUTS 
+% OUTPUTS
 % None
 %
-% REMARKS 
+% REMARKS
 % Contray to the disp method, the whole dseries object is not displayed if the number of
 % observations is greater than 40 and if the number of variables is greater than 10.
 

src/@dseries/end.m

@@ -2,12 +2,12 @@ function lastIndex = end(o, k, n)
 
 % Overloads the end method.
 %
-% INPUTS 
+% INPUTS
 % - o   [dseries]
 % - k   [integer]
 % - n   [integer]
 %
-% OUTPUTS 
+% OUTPUTS
 % - lastIndex   [integer]
 
 % Copyright (C) 2014-2017 Dynare Team

src/@dseries/eq.m

@@ -2,15 +2,15 @@ function b = eq(o, p) % --*-- Unitary tests --*--
 
 % Overloads eq (==) operator.
 %
-% INPUTS 
+% INPUTS
 %  o A      dseries object (T periods, N variables).
 %  o B      dseries object (T periods, N variables).
 %
-% OUTPUTS 
-%  o C      T*N matrix of zeros and ones. Element C(t,n) is nonzero iff observation t of variable n in A and B are equal.  
+% OUTPUTS
+%  o C      T*N matrix of zeros and ones. Element C(t,n) is nonzero iff observation t of variable n in A and B are equal.
 %
-% REMARKS 
-%  If the number of variables, the number of observations or the frequencies are different in A and B, the function returns a zero scalar. 
+% REMARKS
+%  If the number of variables, the number of observations or the frequencies are different in A and B, the function returns a zero scalar.
 
 % Copyright (C) 2013-2017 Dynare Team
 %

src/@dseries/exist.m

@@ -2,12 +2,12 @@ function l = exist(o, varname) % --*-- Unitary tests --*--
 
 % Tests if a variable exists in dseries object o.
 %
-% INPUTS 
+% INPUTS
 %  - o       [dseries], dseries object.
 %  - varname [string],  name of a variable.
 %
-% OUTPUTS 
-%  - l       [logical], equal to 1 (true) iff varname is a variable in dseries object o. 
+% OUTPUTS
+%  - l       [logical], equal to 1 (true) iff varname is a variable in dseries object o.
 
 % Copyright (C) 2014 Dynare Team
 %

src/@dseries/exp.m

@@ -2,10 +2,10 @@ function o = exp(o) % --*-- Unitary tests --*--
 
 % Apply the exponential to all the variables in a dseries object (without in place modification).
 %
-% INPUTS 
+% INPUTS
 % - o [dseries]
 %
-% OUTPUTS 
+% OUTPUTS
 % - o [dseries]
 
 % Copyright (C) 2011-2016 Dynare Team
@@ -41,7 +41,7 @@ o.exp_();
 %$ catch
 %$     t(1) = false;
 %$ end
-%$ 
+%$
 %$ if t(1)
 %$      t(2) = dassert(o, q);
 %$      t(3) = dassert(p.data, ones(10, 2));
@@ -63,7 +63,7 @@ o.exp_();
 %$ catch
 %$     t(1) = false;