Commit dd223e41 authored by Stéphane Adjemian's avatar Stéphane Adjemian
Browse files

Rewrote compute_cova and renamed it nancovariance. Added a new routine to test...

Rewrote compute_cova and renamed it nancovariance. Added a new routine to test if an array contain at least one NaN.
parent 06d1f662
function dataset_ = compute_cova(dataset_) function CovarianceMatrix = nancovariance(data)
% Computes the covariance matrix of the sample (possibly with missing observations). % Computes the covariance matrix of a sample (possibly with missing observations).
%@info: %@info:
%! @deftypefn {Function File} {@var{dataset_} =} compute_corr(@var{dataset_}) %! @deftypefn {Function File} {@var{CovarianceMatrix} =} compute_corr(@var{data})
%! @anchor{compute_corr} %! @anchor{compute_cova}
%! This function computes covariance matrix of the sample (possibly with missing observations). %! This function computes covariance matrix of a sample defined by a dseries object (possibly with missing observations).
%! %!
%! @strong{Inputs} %! @strong{Inputs}
%! @table @var %! @table @var
%! @item dataset_ %! @item data
%! Dynare structure describing the dataset, built by @ref{initialize_dataset} %! a T*N array of real numbers.
%! @end table %! @end table
%! %!
%! @strong{Outputs} %! @strong{Outputs}
%! @table @var %! @table @var
%! @item dataset_ %! @item CovarianceMatrix
%! Dynare structure describing the dataset, built by @ref{initialize_dataset} %! Array of real numbers.
%! @end table %! @end table
%! %!
%! @strong{This function is called by:} %! @strong{This function is called by:}
%! @ref{descriptive_statistics}. %! @ref{descriptive_statistics}.
%! %!
%! @strong{This function calls:} %! @strong{This function calls:}
%! @ref{ndim}, @ref{demean}, @ref{nandemean}. %! @ref{ndim}, @ref{demean}, @ref{nandemean}.
%! %!
%! @strong{Remark 1.} On exit, a new field is appended to the structure: @code{dataset_.descriptive.cova} is a %! @strong{Remark 1.} On exit, a new field is appended to the structure: @code{dataset_.descriptive.cova} is a
%! @tex{n\times n} vector (where @tex{n} is the number of observed variables as defined by @code{dataset_.info.nvobs}). %! @tex{n\times n} vector (where @tex{n} is the number of observed variables as defined by @code{dataset_.info.nvobs}).
%! %!
%! @end deftypefn %! @end deftypefn
%@eod: %@eod:
% Copyright (C) 2011-2012 Dynare Team % Copyright (C) 2011-2014 Dynare Team
% %
% This file is part of Dynare. % This file is part of Dynare.
% %
% Dynare is free software: you can redistribute it and/or modify % Dynare is free software: you can redistribute it and/or modify
...@@ -47,21 +47,55 @@ function dataset_ = compute_cova(dataset_) ...@@ -47,21 +47,55 @@ function dataset_ = compute_cova(dataset_)
% You should have received a copy of the GNU General Public License % You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>. % along with Dynare. If not, see <http://www.gnu.org/licenses/>.
% Original author: stephane DOT adjemian AT univ DASH lemans DOT fr % Initialize the output.
CovarianceMatrix = zeros(size(data,2));
dataset_.descriptive.cova = zeros(dataset_.nvobs);
data = transpose(dataset_.data);
for i=1:dataset_.info.nvobs if isanynan(data)
for j=i:dataset_.info.nvobs data = bsxfun(@minus,data,nanmean(data));
if dataset_.missing.state for i=1:size(data,2)
dataset_.descriptive.cova(i,j) = nanmean(nandemean(data(:,i)).*nandemean(data(:,j))); for j=i:size(data,2)
else CovarianceMatrix(i,j) = nanmean(data(:,i).*data(:,j));
dataset_.descriptive.cova(i,j) = mean(demean(data(:,i)).*demean(data(:,j))); if j>i
end CovarianceMatrix(j,i) = CovarianceMatrix(i,j);
if j>i end
dataset_.descriptive.cova(j,i) = dataset_.descriptive.cova(i,j);
end end
end end
end else
\ No newline at end of file data = bsxfun(@minus,data,mean(data));
CovarianceMatrix = (transpose(data)*data)/size(data,1);
end
%@test:1
%$
%$ % Define a dataset.
%$ data1 = randn(10000000,2);
%$
%$ % Same dataset with missing observations.
%$ data2 = data1;
%$ data2(45,1) = NaN;
%$ data2(57,2) = NaN;
%$ data2(367,:) = NaN(1,2);
%$
%$ t = zeros(2,1);
%$
%$ % Call the tested routine.
%$ try
%$ c1 = nancovariance(data1);
%$ t(1) = 1;
%$ catch
%$ t(1) = 0;
%$ end
%$ try
%$ c2 = nancovariance(data2);
%$ t(2) = 1;
%$ catch
%$ t(2) = 0;
%$ end
%$
%$ if t(1) && t(2)
%$ t(3) = max(max(abs(c1-c2)))<1e-4;
%$ end
%$
%$ % Check the results.
%$ T = all(t);
%@eof:1
\ No newline at end of file
function yes = isanynan(array)
% Return one if the array contains at least one NaN, 0 otherwise.
% Copyright (C) 2011-2014 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/>.
yes = any(isnan(array(:)));
\ No newline at end of file
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