 Usage:  {m,b,const} = intestpl(x,t,y,h,g,loc{,opt})  

 

 Input:



  x                      n x d matrix, the discrete predictor variables. 

                         

  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 , if loc=1 local linear, if 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 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                      ng x pp x q matrix, where pp = p * loc, 

                         containing the marginal integration estimators 

                         of the additive components in the first p columns, 

                         the derivatives in the following. 

                         

  b                      d x 1 matrix, containing the estimators of 

                         the linear factors of the corresponding 

                         linear influences 

                         

  const                  scalar, containing the intercept 

                         

                         

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

