Dear R users,
 
 There is a method called "style analysis" where you make a regression being Y=fund yield and X=benchmarks yield, where we have the restrictions to calculatethe linear regression:
 
 1. The regression must don have the intercept term.
  2. The coefficient sum must be one.
  3. All coefficients must be upper than zero.
 
 These restrictions are necessary to give to regression the sense of percentual  benchmarks contributtions.
  
 Of course the least square method can't do that. So I used the Quadratic Programation method. 
  
 The question is:  How I don't use the least square method, how can I evaluate (without graphics) the good/bad fit?
 
 Another: How can I interpret the exit of the intercept term in the regression?
 
 Thanks
  
  Alexandra
 



  Alexandra R. Mendes de Almeida

                                                 


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

	[[alternative HTML version deleted]]


