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: icatb_gfit2.m
    path of file: ./repos/bspm/thirdparty/MIALAB/GroupICATv4.0a/icatb/icatb_mancovan_files
    
    the code of the file until where you have to start completion: function [gf] = icatb_gfit2(t,y,gFitMeasure,options)
% GFIT2 Computes goodness of fit for regression model
%
% USAGE:
%       [gf] = gfit2(t,y)
%       [gf] = gfit2(t,y,gFitMeasure) 
%       [gf] = gfit2(t,y,gFitMeasure,options)
%
% INPUT:
%           t:  matrix or vector of target values for regression model
%           y:  matrix or vector of output from regression model.
% gFitMeasure:  a string or cell array of string values representing
%               different form of goodness of fit measure as follows:
%               
%               'all' - calculates all the measures below
%               '1' - mean squared error (mse)  
%               '2' - normalised mean squared error (nmse)
%               '3' - root mean squared error (rmse)
%               '4' - normalised root mean squared error (nrmse)
%               '5' - mean absolute error (mae)
%               '6' - mean  absolute relative error  (mare)
%               '7' - coefficient of correlation (r)
%               '8' - coefficient of determination (d)
%               '9' - coefficient of efficiency (e)

    
function [gf] = icatb_gfit2(t,y,gFitMeasure,options)
% GFIT2 Computes goodness of fit for regression model
%
% USAGE:
%       [gf] = gfit2(t,y)
%       [gf] = gfit2(t,y,gFitMeasure) 
%       [gf] = gfit2(t,y,gFitMeasure,options)
%
% INPUT:
%           t:  matrix or vector of target values for regression model
%           y:  matrix or vector of output from regression model.
% gFitMeasure:  a string or cell array of string values representing
%               different form of goodness of fit measure as follows:
%               
%               'all' - calculates all the measures below
%               '1' - mean squared error (mse)  
%               '2' - normalised mean squared error (nmse)
%               '3' - root mean squared error (rmse)
%               '4' - normalised root mean squared error (nrmse)
%               '5' - mean absolute error (mae)
%               '6' - mean  absolute relative error  (mare)
%               '7' - coefficient of correlation (r)
%               '8' - coefficient of determination (d)
%               '9' - coefficient of efficiency (e)
%               '10' - maximum absolute error
%               '11' - maximum absolute relative error
%
%    options: a string containing other output options, currently the only
%             option is verbose output.
%
%                'v' - verbose output, posts some text output for the
%                      chosen measures to the command line
%              
% OUTPUT:
%       gf: vector of goodness of fit values between model output and target for
%       each of the strings in gFitMeasure
%
% EXAMPLES
%
%      gf = gfit2(t,y); for all statistics in list returned as vector
%
%      gf = gfit2(t,y,'3');  for root mean squared error 
%
%      gf = gfit2(t,y, {'3'});  for root mean squared error
%
%      gf = gfit2(t,y, {'1' '3' '9'});  for mean squared error, root mean
%            |                          squared error, and coefficient of 
%           \|/                         efficiency
%      gf = [mse rmse e]
%
%      gf = gfit2(t,y,'all','v'); for all statistics in list returned as
%                                 vector with information posted to the command 
%                                 line on each statistic
%
%      gf = gfit2(t,y, {'1' '3' '9'}, 'v'); for mean squared error, root mean
%                                           squared error, and coefficient of 
%                                           efficiency as a vector with
%                                           information on each of these
%                                           also posted to the command line
%
% Modified from gFit 2008/11/07 by Richard Crozier, extend