R help - Jul 2007 - Implementing Support Vector Regression by ipop in kernlab

Dear R users,
   
  To implement the Support Vector Regression by a general QP, I'm using for
example the function ipop in kernlab package.
  Let me please have some questions for my understanding. In the example for
ipop function, the matrix A includes only variable y. However, in Support Vector
Regression formulation, we have these constraints:
   
  y-f(x)+b<=e
  f(x)+b-y<=e
   
  How vector y does correspond to the matrix A in this formulation? 
   
  How can we include the constant b of above constraints in ipop? 
   
  In the first term of objective function (according to the kernlab package
document), variable x should correspond to slack variables by means of SVR
formulation. However, in the rest of the objective function (quadratic term) ,
variable x corresponds to w in SVR formulation. Therefore, as far as I
understand x corresponds to two variables. Or what is my missing?
   
   
  I thank you so much for your guids. I'm not an expert in this area. Please
help me to understand ipop.
   
  with the best regards,
  T. S.
   

       
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