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    Metadata details:
    filename: rc2ar.m
    path of file: ./repos/malini/Codes/FC_EC_calculation code/DynamicEC/tsa
    
    the code of the file until where you have to start completion: function [MX,res,arg3,acf] = rc2ar(rc);
% converts reflection coefficients into autoregressive parameters
% uses the Durbin-Levinson recursion for multiple channels
% function  [AR,RC,PE,ACF] = rc2ar(RC);
% function  [MX,PE] = rc2ar(RC);
%
%  INPUT:
% RC    reflection coefficients
%
%  OUTPUT
% AR    autoregressive model parameter	
% RC    reflection coefficients (= -PARCOR coefficients)
% PE    remaining error variance (relative to PE(1)=1)
% MX    transformation matrix between ARP and RC (Attention: needs O(p^2) memory)
%        arp=MX(:,K*(K-1)/2+(1:K));
%        rc =MX(:,(1:K).*(2:K+1)/2);
%
% All input and output parameters are organized in rows, one row 
% corresponds to the parameters of one channel
%
% see also ACOVF ACORF DURLEV AR2RC 
% 
% REFERENCES:
%  P.J. Brockwell and R. A. Davis "Time Series: Theory and Methods", 2nd ed. Springer, 1991.
%  S. Haykin "Adaptive Filter Theory" 3rd ed. Prentice Hall, 1996.
%  M.B. Priestley "Spectral Analysis and Time Series" Academic Press, 1981. 
%  W.S. Wei "Time Series Analysis" Addison Wesley, 1990.


    
function [MX,res,arg3,acf] = rc2ar(rc);
% converts reflection coefficients into autoregressive parameters
% uses the Durbin-Levinson recursion for multiple channels
% function  [AR,RC,PE,ACF] = rc2ar(RC);
% function  [MX,PE] = rc2ar(RC);
%
%  INPUT:
% RC    reflection coefficients
%
%  OUTPUT
% AR    autoregressive model parameter	
% RC    reflection coefficients (= -PARCOR coefficients)
% PE    remaining error variance (relative to PE(1)=1)
% MX    transformation matrix between ARP and RC (Attention: needs O(p^2) memory)
%        arp=MX(:,K*(K-1)/2+(1:K));
%        rc =MX(:,(1:K).*(2:K+1)/2);
%
% All input and output parameters are organized in rows, one row 
% corresponds to the parameters of one channel
%
% see also ACOVF ACORF DURLEV AR2RC 
% 
% REFERENCES:
%  P.J. Brockwell and R. A. Davis "Time Series: Theory and Methods", 2nd ed. Springer, 1991.
%  S. Haykin "Adaptive Filter Theory" 3rd ed. Prentice Hall, 1996.
%  M.B. Priestley "Spectral Analysis and Time Series" Academic Press, 1981. 
%  W.S. Wei "Time Series Analysis" Addison Wesley, 1990.

%	$Id: rc2ar.m 5090 2008-06-05 08:12:04Z schloegl $
%	Copyright (c) 1996-2002,2007,2008 by Alois Schloegl <a.schloegl@ieee.org>
%       This function is part of the TSA-toolbox
%       http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/tsa/
%
%    This program 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.
%
%    This program 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 this program.  If not, see <http://www.gnu.org/licenses/>.


% Inititialization
[lr,lc]=size(rc);
res=[ones(lr,1) zeros(lr,lc)];
if nargout<3         % needs O(p^2) memory 
        MX=zeros(lr,lc*(lc+1)/2);   
        idx=0;
        
        % Durbin-Levinson Algorithm
        for K=1:lc,
                MX(:,idx+K)=rc(:,K);%(AutoCov(:,K+1)-d)./res(:,K);
                %rc(:,K)=arp(:,K);
                if K>1   %for compatibility with OCTAVE 2.0.13
                        MX(:,idx+(1:K-1))=MX(:,(K-2)*(K-1)/2+(1:K-1))-MX(:,(idx+K)*ones(K-1,1)).*MX(:,(K-2)*(K-1)/2+(K-1:-1:1));
                end