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: multigarchSimulate.m
    path of file: ./repos/malini/Codes/FC_EC_calculation code/DynamicFC/jplv7/Ucsd_garch/Garch
    
    the code of the file until where you have to start completion: function [data,h]=multigarchsimulate(T,parameters,p,o,q,type,errors,nu2)
% PURPOSE:
%     Simulate the models of multi_garch
% 
% USAGE:
%     [data,h]=multigarchsimulate(T,parameters,p,o,q,type,errors,nu2)
% 
% INPUTS:
%     t: Length of the time series desired
%     parameters: a 1+p+q x 1 vector of inputs where p are ARCH coefs and Q are GARCH coefs
%     P: Positive, scalar integer representing a model order of the ARCH process
%     O: Non-Negative order of the assymetric news impact parameters 
%     Q: Non-Negative scalar integer representing a model order of the GARCH 
%        process: Q is the number of lags of the lagged conditional variances included
%        Can be empty([]) for ARCH process
%    type: One of the types below denoting the type of GARCH
%    errors: Either 'NORMAL', 'STUDENTST', or 'GED', a string
%    nu2: If T or GED are selected the shape parameter
% 
% OUTPUTS:
%     data - T by 1 vector of residuals
%     h - Time-varying variance
% 
% COMMENTS:
%                  Without assymetric terms
%    'GARCH'    -  Normal GARCH Model(see garchpq or fattailed_garch instead) 
%    'AVGARCH'  -  Absolute Value GARCH                   
%    'NGARCH'   -  Non-linear GARCH                       
%    'NAGARCH'  -  Non-Linear Asymetric GARCH             
%                  With assymetric terms
%    'EGARCH'   -  Exponential GARCH                      
%    'TGARCH'   -  Threshold GARCH                        
%    'GJRCARCH' -  GJR Representation of TARCH                    
%    'APGARCH'  -  Asymetric Power GARCH                  
%    'ALLGARCH' -  Asymetric Power GARCH with news impact centering parameter 
% 
% Author: Kevin Sheppard
% kevin.sheppard@economics.ox.ac.uk
% Revision: 2    Date: 12/31/2001

T=T+500;
parameters(find(parameters(1:1+p+q+o) <= 0)) = realmin;
garchparameters=parameters(1:p+q+o+1);
remainingparams=parameters(p+q+2:length(parameters));
constp=garchparameters(1);
archp=garchparameters(2:p+1);
tarchp=garchparameters(p+2:p+o+1);
garchp=garchparameters(p+o+2:p+q+o+1);

if strcmp(type,'GARCH')
    lambda=2;
    nu=2;
    b=0;
elseif strcmp(type,'TGARCH');
    lambda=1;
    nu=1;
    b=0;
elseif strcmp(type,'AVGARCH');
    lambda=1;
    nu=1;

    
function [data,h]=multigarchsimulate(T,parameters,p,o,q,type,errors,nu2)
% PURPOSE:
%     Simulate the models of multi_garch
% 
% USAGE:
%     [data,h]=multigarchsimulate(T,parameters,p,o,q,type,errors,nu2)
% 
% INPUTS:
%     t: Length of the time series desired
%     parameters: a 1+p+q x 1 vector of inputs where p are ARCH coefs and Q are GARCH coefs
%     P: Positive, scalar integer representing a model order of the ARCH process
%     O: Non-Negative order of the assymetric news impact parameters 
%     Q: Non-Negative scalar integer representing a model order of the GARCH 
%        process: Q is the number of lags of the lagged conditional variances included
%        Can be empty([]) for ARCH process
%    type: One of the types below denoting the type of GARCH
%    errors: Either 'NORMAL', 'STUDENTST', or 'GED', a string
%    nu2: If T or GED are selected the shape parameter
% 
% OUTPUTS:
%     data - T by 1 vector of residuals
%     h - Time-varying variance
% 
% COMMENTS:
%                  Without assymetric terms
%    'GARCH'    -  Normal GARCH Model(see garchpq or fattailed_garch instead) 
%    'AVGARCH'  -  Absolute Value GARCH                   
%    'NGARCH'   -  Non-linear GARCH                       
%    'NAGARCH'  -  Non-Linear Asymetric GARCH             
%                  With assymetric terms
%    'EGARCH'   -  Exponential GARCH                      
%    'TGARCH'   -  Threshold GARCH                        
%    'GJRCARCH' -  GJR Representation of TARCH                    
%    'APGARCH'  -  Asymetric Power GARCH                  
%    'ALLGARCH' -  Asymetric Power GARCH with news impact centering parameter 
% 
% Author: Kevin Sheppard
% kevin.sheppard@economics.ox.ac.uk
% Revision: 2    Date: 12/31/2001

T=T+500;
parameters(find(parameters(1:1+p+q+o) <= 0)) = realmin;
garchparameters=parameters(1:p+q+o+1);
remainingparams=parameters(p+q+2:length(parameters));
constp=garchparameters(1);
archp=garchparameters(2:p+1);
tarchp=garchparameters(p+2:p+o+1);
garchp=garchparameters(p+o+2:p+q+o+1);

if strcmp(type,'GARCH')
    lambda=2;
    nu=2;
    b=0;
elseif strcmp(type,'TGARCH');
    lambda=1;
    nu=1;
    b=0;
elseif strcmp(type,'AVGARCH');
    lambda=1;
    nu=1;
    b=remainingparams(1);
elseif strcmp(type,'NGARCH')
    lambda=remainingparams(1);
    nu=lambda;
    b=0;
elseif strcmp(type,'NAGARCH')
    lambda=2;
    nu=2;
    b=remainingparams(1);
elseif strcmp(type,'APGARCH')
    lambda=remainingparams(1);
    nu=lambda;
    b=0;
elseif strcmp(type,'ALLGARCH')
    lambda=remainingparams(1);
    nu=lambda;
    b=remainingparams(2);
elseif strcmp(type,'GJRGARCH')
    lambda=2;
    nu=2;
    b=0;
else
    error('Do not know hwo to simulate that GARCH')
end