Hi, Simon,
Thank you very much for the helpful suggestion. But if the model is a
partially linear model, i.e.
y(x1)=a0+a1*x1+a2*x2+a3*s(x3)where x1 is the decision variable
I would like to evaluate y(x1) at a specific level of x2 and x3 (i.e. y is a
function of x1 only). In doin
On Sunday 15 April 2007 23:36, Jin Huang wrote:
> Dear all,
>
> I fitted a non-parametric model using GAM function in R. i.e.,
> gam(y~s(x1)+s(x2)) #where s() is the smooth function
> Then I obtained the coefficients(a and b) for the non-parametric terms.
> i.e., y=a*s(x1)+b*s(x2)
-- do you
Dear all,
I fitted a non-parametric model using GAM function in R. i.e.,
gam(y~s(x1)+s(x2)) #where s() is the smooth function
Then I obtained the coefficients(a and b) for the non-parametric terms. i.e.,
y=a*s(x1)+b*s(x2)
Now if I want to use this estimated model to do optimiza
