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: correl_compare_indep.m
    path of file: ./repos/CanlabCore/CanlabCore/Statistics_tools
    
    the code of the file until where you have to start completion: function [r1, r2, rdiff, rdiff_p, rdiff_zscore] = correl_compare_indep(y_g1, y_g2, varargin)
% Compute statistics on the difference between correlation coefficients
% for indepndent samples g1 and g2.
%
% :Usage:
% ::
%
%     [r1, r2, rdiff, rdiff_p, rdiff_zscore] = correl_compare_indep(y_g1, y_g2, varargin)
%
% Correlations are computed over y (n observations x k variables) for each
% group.
%
% Source, Hubert Blalock, Social Statistics, NY: McGraw-Hill, 1972:  406-407.
% From notes on Garson stats website.
%
%
% :Inputs:
%
%   **y_g1:**
%        Matrix of variables for group 1 (n observations x k variables)
%
%   **y_g2:**
%        Matrix of variables for group 2 (n observations x k variables)
%     
% :Optional Inputs:
%
%   **varargin:**
%        String 'noverbose' can be used to prevent output from being
%        printed to command line
%

    
function [r1, r2, rdiff, rdiff_p, rdiff_zscore] = correl_compare_indep(y_g1, y_g2, varargin)
% Compute statistics on the difference between correlation coefficients
% for indepndent samples g1 and g2.
%
% :Usage:
% ::
%
%     [r1, r2, rdiff, rdiff_p, rdiff_zscore] = correl_compare_indep(y_g1, y_g2, varargin)
%
% Correlations are computed over y (n observations x k variables) for each
% group.
%
% Source, Hubert Blalock, Social Statistics, NY: McGraw-Hill, 1972:  406-407.
% From notes on Garson stats website.
%
%
% :Inputs:
%
%   **y_g1:**
%        Matrix of variables for group 1 (n observations x k variables)
%
%   **y_g2:**
%        Matrix of variables for group 2 (n observations x k variables)
%     
% :Optional Inputs:
%
%   **varargin:**
%        String 'noverbose' can be used to prevent output from being
%        printed to command line
%
% :Outputs:
%
%   **r1:**
%        Matrix of correlation coefficients for group 1
%
%   **r2:**
%        Matrix of correlation coefficients for group 2
%
%   **rdiff:**
%        Difference in correlation coefficient matrices (r1 - r2)
%
%   **rdiff_p:**
%        p values testing against no difference between r1 and r2. 
%        Hubert Blalock, Social Statistics, NY: McGraw-Hill, 1972:  406-407.
%
%   **rdiff_zscore:**
%        z scores for the difference between r1 and r2. 
%
% :Examples:
% ::
%
%    %generate two random input matrices (20 subjects x 5 variables)
%    y_g1 = rand(20,5);
%    y_g2 = rand(20,5);
%    [r1, r2, rdiff, rdiff_p, rdiff_zscore] = correl_compare_indep(y_g1,y_g2);
%
%    %supress output
%    [r1, r2, rdiff, rdiff_p, rdiff_zscore] = correl_compare_indep(y_g1,y_g2,'noverbose');
%
%
% :See also:
%   - correl_compare_indep_inputr, correl_compare_permute*
%
% ..
%    Tor Wager, Aug. 2008
%
%    Edit: March 2010-add no verbose option.  input 'noverbose'
%    Bug fix in Fisher's Z transform
% ..

    verbose = 1;
    if length(varargin) > 0
        for i = 1:length(varargin)
            if ischar(varargin{i})
                switch varargin{i}
                    case 'noverbose', verbose = 0;

                    otherwise, warning(['Unknown input string option:' varargin{i}]);
                end