 Usage:  testt = intertest2(t,y,h,g{,opt{,file}})  
 
 Input:

  t                      n x p matrix , the observed explanatory variable 
                         where the directions of interest have to be the 
                         first and second column 
                         
  y                      n x 1 vector , the observed 
                         response variables 
                         
  h                      2 x 1 or 1 x 1 matrix , chosen bandwidth for 
                         the directions of interest in the estimation step 
                         
  g                      p x 1 or 1 x 1 matrix , chosen bandwidth for 
                         the directions not of interest in the estimation step 
                         
  opt.hyp                pp x 2 matrix, in the rows have to be all pairs 
                         of indices for interactions which shall be included 
                         in the hypothesis model. Thus (1,2) must not be 
                         a row of hyp. 
                         
  opt.boot               integer, number of bootstrap replications, default=249. 
                         
  opt.hb                 scalar, bandwidth multiplicator for the bootstrap 
                         step. When the test statistics are calculated with 
                         estimating the derivative we take bandwidths h*hb 
                         and g*hb instead of h, g. Default is 1. 
                         
  opt.weight             n x 1 vector, weights for the test statistics. 
                         Default is weight 1 for all. 
                         
  opt.loc                integer from {1,2}, degree for the local polynomial 
                         smoother, default is linear (loc=1) 
                         
  file                   string, file name of output, if an output of 
                         the function estimates is wished 
                         
 Output:

  testt                  string object, a table of results 
                         
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(C) MD*TECH Method and Data Technologies, 17.8.2000
