 Usage:  mssr = prederr (tr, x, y, type)  

 

 Input:



  tr                     list of vectors: data structure which represents a binary tree 

                         and is produced by cartsplit procedure, contains vectors 

                         tr.val, tr.vec, tr.mean, tr.ssr, tr.nelem. 

                         See cartsplit for the description of tr. 

                         

  x                      n x p vector: represents n points in the sample space 

                         at which the prediction of the regression tree will 

                         be calculated. 

                         

  y                      n x 1 vector: 

                         contains the values of the response variable. 

                         

  type                   p x 1 vector: 

                         contains the types of the original regression variables, 

                         1 means that the corresponding variable is continuous and 

                         0 that it is categorical. This vector should be similar to 

                         the vector which was given originally as an input to the 

                         cartsplit which produced the regression tree tr. 

                         

 Output:



  mssr                   real number >0: 

                         mean of the squared residuals, that is, 

                         sum of squared differences between predictions and 

                         observations, divided by the number of observations n. 

                         

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

