Reputation: 119
I would like to apply a gam model on a dataset with specifying the types of functions to use.
It would be something like :
y ~ cst1 * (s(var1)-s(var2)) * (1 - exp(var3*cst2))
s
has to be the same function for both var1
and var2
. I don't have a prior idea on s
function family. If I resume, the model would find the constants (cst1
and cst2
) plus the function s
.
Is it possible? If not, is there any way (another type of models) i can use to do what i'm looking for?
Thanks in advance for replies.
Upvotes: 0
Views: 297
Reputation: 36
This model could be fit with nls
, the non-linear least squares package. This will allow you to model the formula you want directly. The splines will need to be done manually, though. This question gets at what you would be trying to do.
As far as getting the splines to be the same for var1
and var2
, you can do this by subtracting the basis matrices. Basically you want to compute the coefficient vector A
where the term is A * s(var1) + A * s(var2) = A * (s(var1) - s(var2))
. You wouldn't want to just do s(var1 - var2)
; in general, f(x) - f(y) != f(x - y)
. To do this in R, you would
Compute the spline basis matrices with ns()
for var1
and var2
, giving them the same knots. You need to specify both the knots
and the Boundary.knots
parameters so that the two splines will share the same basis.
Subtract the two spline basis matrices (the output from the ns()
function).
Adapt the resulting subtracted spline basis matrix for the nls
formula, as they do in the question I linked earlier.
Upvotes: 1