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Renamed compute_stdv as nanvariance (computes variances instead of standard deviations).

time-shift
Stéphane Adjemian (Charybdis) 2014-05-23 18:06:32 +02:00
parent bdd7b8aacc
commit b2c28530ea
1 changed files with 12 additions and 14 deletions
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26
matlab/utilities/dataset/compute_stdv.m → matlab/utilities/dataset/nanvariance.m
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@ -1,21 +1,21 @@
function dataset_ = compute_stdv(dataset_)
function variances = nanvariance(data)
% Compute the standard deviation for each observed variable (possibly with missing observations).
%@info:
%! @deftypefn {Function File} {@var{dataset_} =} compute_stdv(@var{dataset_})
%! @anchor{compute_stdv}
%! This function computes the standard deviation of the observed variables (possibly with missing observations).
%! @deftypefn {Function File} {@var{variances} =} nanvariance(@var{data})
%! @anchor{nanvariance}
%! This function computes the variances of the observed variables (possibly with missing observations).
%!
%! @strong{Inputs}
%! @table @var
%! @item dataset_
%! Dynare structure describing the dataset, built by @ref{initialize_dataset}
%! @item datas
%! A T*N array of real numbers.
%! @end table
%!
%! @strong{Outputs}
%! @table @var
%! @item dataset_
%! Dynare structure describing the dataset, built by @ref{initialize_dataset}
%! @item variances
%! A N*1 vector of real numbers
%! @end table
%!
%! @strong{This function is called by:}
@ -30,7 +30,7 @@ function dataset_ = compute_stdv(dataset_)
%! @end deftypefn
%@eod:
% Copyright (C) 2011-2012 Dynare Team
% Copyright (C) 2011-2014 Dynare Team
%
% This file is part of Dynare.
%
@ -47,10 +47,8 @@ function dataset_ = compute_stdv(dataset_)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
% Original author: stephane DOT adjemian AT univ DASH lemans DOT fr
if dataset_.missing.state
dataset_.descriptive.stdv = sqrt(nanmean(bsxfun(@power,nandemean(transpose(dataset_.data)),2)));
if isanynan(data)
variances = transpose(nanmean(bsxfun(@power,nandemean(data),2)));
else
dataset_.descriptive.stdv = sqrt(mean(bsxfun(@power,demean(transpose(dataset_.data)),2)));
variances = transpose(mean(bsxfun(@power,demean(data),2)));
end