 Usage:  m = gintest(code,t,y,h,g,loc{,opt})  

 

 Input:



  code                   string, specifying the code function 

                         implemented codes: noid, bipro, bilo 

                         

  t                      n x p matrix, the continuous predictor variables. 

                         

  y                      n x q matrix , the observed 

                         response variables 

                         

  h                      p x 1 or 1 x 1 matrix , chosen bandwidth for 

                         the directions of interest 

                         

  g                      p x 1 or 1 x 1 matrix , chosen bandwidth for 

                         the directions not of interest 

                         

  loc                    dummy , for loc=0 local constant (Nad. Wats.), 

                         for loc=1 local linear and for loc=2 local 

                         quadratic estimator will be used 

                         

  opt                    optional, a list with optional input. The macro 

                         "gplmopt" can be used to set up this parameter. 

                         The order of the list elements is not important. 

                         Parameters which are not given are replaced by 

                         defaults (see below). 

                         

  opt.tg                 ng x pg vector, a grid for continuous part. If tg is 

                         given, the nonparametric function will also be 

                         computed on this grid. 

                         

  opt.shf                integer, (show-how-far) if exists and =1, an output 

                         is produced which indicates how the iteration 

                         is going on (additive function / point of estimation / 

                         number of iteration). 

                         

 Output:



  m                      n(ng) x p(pg) x q matrix, containing the marginal 

                         integration estimators 

                         

--------------------------------------------------------------

(C) MD*TECH Method and Data Technologies, 21.9.2000

