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: lo_like.m
    path of file: ./repos/malini/Codes/FC_EC_calculation code/DynamicFC/jplv7/regress
    
    the code of the file until where you have to start completion: function out = lo_like(b,y,x)
% PURPOSE: evaluate logit log-likelihood
%-----------------------------------------------------
% USAGE:    like = lo_like(b,y,x,flag) 
% where:     b = parameter vector (k x 1)
%            y = dependent variable vector (n x 1)
%            x = explanatory variables matrix (n x m)
%-----------------------------------------------------
% NOTE: this function returns a scalar
%       k ~= m because we may have additional parameters
%           in addition to the m bhat's (e.g. sigma)
%-----------------------------------------------------
% SEE also: h
    
function returns a scalar
%       k ~= m because we may have additional parameters
%           in addition to the m bhat's (e.g. sigma)
%-----------------------------------------------------
% SEE also: hessian, gradnt, gradt
%-----------------------------------------------------
% REFERENCES: Green, 1997 page 883
%-----------------------------------------------------

% written by:
% James P. LeSage, Dept of Economics
% University of Toledo
% 2801 W. Bancroft St,
% Toledo, OH 43606
% jpl@jpl.econ.utoledo.edu


i = ones(length(y),1);
cdf = i./(i+exp(-x*b));
tmp = find(cdf <=0);
[n1 n2] = size(tmp);
if n1 ~= 0
cdf(tmp) = 0.00001;
end