On May 4, 2013, at 10:26 PM, Preetam Pal wrote:
Thanks David for the paper, I understand the theory.
But my question is about R only: the vector of coefficients that R outputs in
lars(), does it apply against the original variable y or against (y-y_bar). I
have put in intercept=T as well
Hi all,
I have a data set containing variables LOSS, GDP, HPI and UE.
(I have attached it in case it is required).
Having renamed the variables as l,g,h and u, I wish to run a Lasso
Regression with l as the dependent variable and all the other 3 as the
independent variables.
On May 4, 2013, at 6:09 AM, Preetam Pal wrote:
Hi all,
I have a data set containing variables LOSS, GDP, HPI and UE.
(I have attached it in case it is required).
Having renamed the variables as l,g,h and u, I wish to run a Lasso
Regression with l as the dependent variable and all the
Hi,
I rectified my error (thanks David for pointing it out)
Now I have been able to run the code:
data=read.table(data.txt, header=T)
l=data$LOSS
h=data$HPI
u=data$UE
g=data$GDP
matrix=cbind(g,h,u)
lasso=lars(matrix,l)
The final set of coefficients for the regression is the last row of
Thanks David for the paper, I understand the theory.
But my question is about R only: the vector of coefficients that R outputs
in lars(), does it apply against the original variable y or against
(y-y_bar). I have put in intercept=T as well in my lars() model.
I need this information to calculate
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