You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: cov1para.m
    path of file: ./repos/brainstorm3/external/scilearnlab/private
    
    the code of the file until where you have to start completion: function [sigma,shrinkage]=cov1para(x,shrink)

% function sigma=cov1para(x)
% x (t*n): t iid observations on n random variables
% sigma (n*n): invertible covariance matrix estimator
%
% Shrinks towards one-parameter matrix:
%    all variances are the same
%    all covariances are zero
% if shrink is specified, then this value is used for shrinkage

% This version: 04/2014

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is released under the BSD 2-clause license.

% Copyright (c) 2014, Olivier Ledoit and Michael Wolf 
% All rights reserved.
% 
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are
% met:

    
function [sigma,shrinkage]=cov1para(x,shrink)

% function sigma=cov1para(x)
% x (t*n): t iid observations on n random variables
% sigma (n*n): invertible covariance matrix estimator
%
% Shrinks towards one-parameter matrix:
%    all variances are the same
%    all covariances are zero
% if shrink is specified, then this value is used for shrinkage

% This version: 04/2014

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is released under the BSD 2-clause license.

% Copyright (c) 2014, Olivier Ledoit and Michael Wolf 
% All rights reserved.
% 
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are
% met:
% 
% 1. Redistributions of source code must retain the above copyright notice,
% this list of conditions and the following disclaimer.
% 
% 2. Redistributions in binary form must reproduce the above copyright
% notice, this list of conditions and the following disclaimer in the
% documentation and/or other materials provided with the distribution.
% 
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
% IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
% THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
% PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
% CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
% EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
% PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
% PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
% LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
% NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


% de-mean returns
[t,n]=size(x);
meanx=mean(x);
x=x-meanx(ones(t,1),:);
%x = bsxfun(@minus,x,meanx);

% compute sample covariance matrix
sample=(1/t).*(x'*x);

% compute prior
%meanvar=mean(diag(sample));
meanvar = trace(sample)/n;
prior=meanvar*eye(n);

%if (nargin < 2 | shrink == -1) % compute shrinkage parameters
  
  % what we call p 
  y=x.^2;
  phiMat=y'*y/t-sample.^2;
  phi=sum(sum(phiMat));
  
  % what we call r is not needed for this shrinkage target
  
  % what we call c
  %gamma=norm(sample-prior,'fro')^2;
  gamma = sample-prior;
  gamma = sum(gamma(:).^2);

  % compute shrinkage constant
  kappa=phi/gamma;
  shrinkage=max(0,min(1,kappa/t));
    
%else % use specified number
%  shrinkage=shrink;
%end