Added mean and std methods.

Returns the arithmetic or geometric mean and standard deviation.

(cherry picked from commit b8547bc8)

src/@dseries/mean.m

+function m = mean(o, geometric) % --*-- Unitary tests --*--
+
+% Returns the mean of the variables in a @dseries object o.
+%
+% INPUTS
+%  o o             dseries object [mandatory].
+%  o geometric     logical [default is false], if true returns the geometric mean.
+%
+% OUTPUTS
+%  o m             1*vobs(o) vector of doubles.
+
+% Copyright (C) 2016 Dynare Team
+%
+% This file is part of Dynare.
+%
+% Dynare is free software: you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation, either version 3 of the License, or
+% (at your option) any later version.
+%
+% Dynare is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+% GNU General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
+
+if nargin<2
+    geometric = false;
+end
+
+if geometric
+    m = prod(o.data, 1).^(1/nobs(o));
+else
+    m = mean(o.data);
+end
+
+%@test:1
+%$ % Define a dataset.
+%$ A = repmat([1.005, 1.05], 10, 1);
+%$
+%$ % Instantiate a time series object and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    m = mean(ts, true);
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(m),[1, 2]), true);
+%$    t(3) = dassert(m, [1.005, 1.05]);
+%$ end
+%$ T = all(t);
+%@eof:1
+
+%@test:2
+%$ % Define a dataset.
+%$ A = repmat([1.005, 1.05], 10, 1);
+%$
+%$ % Instantiate a time series object and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    m = ts.mean(true);
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(m),[1, 2]), true);
+%$    t(3) = dassert(m, [1.005, 1.05]);
+%$ end
+%$ T = all(t);
+%@eof:2
+
+%@test:3
+%$ % Define a dataset.
+%$ A = bsxfun(@plus, randn(100000000,2)*.1, [.5, 2]);
+%$
+%$ % Instantiate time series objects and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    m1 = mean(ts);
+%$    m2 = mean(ts, true);
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(m1),[1, 2]), true);
+%$    t(3) = dassert(isequal(size(m2),[1, 2]), true);
+%$    t(4) = dassert(max(abs(m1-[.5, 2]))<.0001, true);
+%$    t(5) = isinf(m2(2));
+%$    t(6) = isequal(m2(1), 0);
+%$ end
+%$ T = all(t);
+%@eof:3
+
+%@test:4
+%$ % Define a dataset.
+%$ A = bsxfun(@plus, randn(100000000,2)*.1, [.5, 2]);
+%$
+%$ % Instantiate time series objects and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    m1 = ts.mean();
+%$    m2 = ts.mean(true);
+%$    m3 = ts.mean(false);
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(m1),[1, 2]), true);
+%$    t(3) = dassert(isequal(size(m2),[1, 2]), true);
+%$    t(4) = dassert(max(abs(m1-[.5, 2]))<.0001, true);
+%$    t(5) = isinf(m2(2));
+%$    t(6) = isequal(m2(1), 0);
+%$    t(7) = isequal(m1, m3);
+%$ end
+%$ T = all(t);
+%@eof:4
\ No newline at end of file

src/@dseries/std.m

+function s = std(o, geometric) % --*-- Unitary tests --*--
+
+% Returns the standard deviation of the variables in a @dseries object o.
+% See https://en.wikipedia.org/wiki/Geometric_standard_deviation
+%
+% INPUTS
+%  o o             dseries object [mandatory].
+%  o geometric     logical [default is false], if true returns the geometric standard deviation.
+%
+% OUTPUTS
+%  o s             1*vobs(o) vector of doubles.
+
+% Copyright (C) 2016 Dynare Team
+%
+% This file is part of Dynare.
+%
+% Dynare is free software: you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation, either version 3 of the License, or
+% (at your option) any later version.
+%
+% Dynare is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+% GNU General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
+
+if nargin<2
+    geometric = false;
+end
+
+if geometric
+    m = mean(o, true);
+    s = exp(sqrt(sum(log(bsxfun(@rdivide, o.data, m)).^2, 1)/nobs(o)));
+else
+    s = std(o.data);
+end
+
+%@test:1
+%$ % Define a dataset.
+%$ A = repmat([1.005, 1.05], 10, 1);
+%$
+%$ % Instantiate a time series object and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    s1 = std(ts, true);
+%$    s2 = std(ts);
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(s1),[1, 2]), true);
+%$    t(3) = dassert(isequal(size(s2),[1, 2]), true);
+%$    t(4) = dassert(s1, [1, 1]);
+%$    t(4) = all(abs(s2)<1e-12);
+%$ end
+%$ T = all(t);
+%@eof:1
+
+%@test:2
+%$ % Define a dataset.
+%$ A = repmat([1.005, 1.05], 10, 1);
+%$
+%$ % Instantiate a time series object and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    s1 = ts.std(true);
+%$    s2 = ts.std();
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(s1),[1, 2]), true);
+%$    t(3) = dassert(isequal(size(s2),[1, 2]), true);
+%$    t(4) = dassert(s1, [1, 1]);
+%$    t(4) = all(abs(s2)<1e-12);
+%$ end
+%$ T = all(t);
+%@eof:2
+
+%@test:3
+%$ % Define a dataset.
+%$ A = bsxfun(@plus, randn(100000000,2)*.1, [.5, 2]);
+%$
+%$ % Instantiate time series objects and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    s = std(ts);
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$ 
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(s),[1, 2]), true);
+%$    t(3) = dassert(max(abs(s-[.1, .1]))<.0001, true);
+%$ end
+%$ T = all(t);
+%@eof:3
+
+%@test:4
+%$ % Define a dataset.
+%$ A = bsxfun(@plus, randn(100000000,2)*.1, [.5, 2]);
+%$
+%$ % Instantiate time series objects and compute the mean.
+%$ try
+%$    ts = dseries(A);
+%$    s = ts.std();
+%$    t(1) = 1;
+%$ catch
+%$    t = 0;
+%$ end
+%$ 
+%$ if t(1)
+%$    t(2) = dassert(isequal(size(s),[1, 2]), true);
+%$    t(3) = dassert(max(abs(s-[.1, .1]))<.0001, true);
+%$ end
+%$ T = all(t);
+%@eof:4
\ No newline at end of file

src/@dseries/subsref.m

@@ -90,7 +90,7 @@ switch S(1).type
       case 'freq'
         % Returns an integer characterizing the data frequency (1, 4, 12 or 52)
         B = A.dates.freq;
-      case {'lag','lead','hptrend','hpcycle','chain','detrend','exist'} % Methods with less than two arguments.
+      case {'lag','lead','hptrend','hpcycle','chain','detrend','exist','mean','std'} % Methods with less than two arguments.
         if length(S)>1 && isequal(S(2).type,'()')
             if isempty(S(2).subs)
                 B = feval(S(1).subs,A);