# Matlab-genNoisyData
function to generate a dataset with m realisations of a random d-dimensional variable with given covariance matrix
```Matlab
function dataM = genCovData(covM, m, y0)
% Keywords: covariance, random data, noisy data
%
% Purpose : generate a data set with m random data vectors with a
% exactly the predefined covariance matrix 'covM'; optional a
% datavector can be given to generate a noisy data set for. In
% this case the generated noise is added to y0
%
% Syntax : dataM = genCovData(covM, m)
% dataM = genCovData(covM, m, y0)
%
% Input Parameters :
% covM := covariancematrix of the output; a squared symmetric
% positiv semi-definit matrix; dimension d of the matrix is the
% dimension of the random data vector
%
% m := number of realisations of random data vector;
%
% y0 := a column vector of size [dx1]; to this vector, the
% generated noise with given covariance is added.
%
%
% Return Parameters :
% dataM := a matrix of size [dxm], where each column is a
% realisation of the random variable; the covariance (cov(dataM')
% is the given covM;
%
% Description :
% using code from:
% https://stats.stackexchange.com/questions/120179/generating-data-with-a-given-sample-covariance-matrix
% see also: mvnrnd
% Author :
% Roland Ritt
%
% History :
% \change{1.0}{29-Jun-2017}{Original}
%
% --------------------------------------------------
% (c) 2017, Roland Ritt
% Chair of Automation, University of Leoben, Austria
% email: automation@unileoben.ac.at
% url: automation.unileoben.ac.at
% --------------------------------------------------
```