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: f_sar.m
    path of file: ./repos/malini/Codes/FC_EC_calculation code/DynamicFC/jplv7/spatial/sar_models
    
    the code of the file until where you have to start completion: function llike = f_sar(rho,detval,epe0,eped,epe0d,n)
% PURPOSE: evaluates concentrated log-likelihood for the 
%  spatial autoregressive model using sparse matrix algorithms
% ---------------------------------------------------
%  USAGE:llike = f_sar(rho,detval,epe0,eped,epe0d,n)
%  where: rho  = spatial autoregressive parameter
%         detval = a matrix with vectorized log-determinant information
%         epe0   = see below
%         eped   = see below
%         eoe0d  = see below
%         n      = # of obs

    
function llike = f_sar(rho,detval,epe0,eped,epe0d,n)
% PURPOSE: evaluates concentrated log-likelihood for the 
%  spatial autoregressive model using sparse matrix algorithms
% ---------------------------------------------------
%  USAGE:llike = f_sar(rho,detval,epe0,eped,epe0d,n)
%  where: rho  = spatial autoregressive parameter
%         detval = a matrix with vectorized log-determinant information
%         epe0   = see below
%         eped   = see below
%         eoe0d  = see below
%         n      = # of obs
%          b0 = AI*xs'*ys;
%          bd = AI*xs'*Wys;
%          e0 = ys - xs*b0;
%          ed = Wys - xs*bd;
%          epe0 = e0'*e0;
%          eped = ed'*ed;
%          epe0d = ed'*e0;
% ---------------------------------------------------
%  RETURNS: a  scalar equal to minus the log-likelihood
%           function value at the parameter rho
% ---------------------------------------------------                         
%  NOTE: this is really two functions depend