function variances = nanvariance(data) % Compute the standard deviation for each observed variable (possibly with missing observations). %@info: %! @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 datas %! A T*N array of real numbers. %! @end table %! %! @strong{Outputs} %! @table @var %! @item variances %! A N*1 vector of real numbers %! @end table %! %! @strong{This function is called by:} %! @ref{descriptive_statistics}. %! %! @strong{This function calls:} %! @ref{ndim}, @ref{demean}, @ref{nandemean}. %! %! @strong{Remark 1.} On exit, a new field is appended to the structure: @code{dataset_.descriptive.stdv} is a %! @tex{n\times 1} vector (where @tex{n} is the number of observed variables as defined by @code{dataset_.info.nvobs}). %! %! @end deftypefn %@eod: % Copyright © 2011-2017 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 . if isanynan(data) variances = transpose(nanmean(bsxfun(@power,nandemean(data),2))); else variances = transpose(mean(bsxfun(@power,demean(data),2))); end