Is there a way in glmnet to do first order interactions?
For instance, if my X matrix was:
V1 V2 V3
0 1 0
1 0 1
1 0 0
...
Is there a way to specify that it do something along the lines of `y~ V1 + V2 + V3 + V1*V2 + V2 *V3 + V1*V3' without manually creating the columns? My actual matrix is larger and would be a pain to create all first order cross products by hand.
The proper R syntax for such a formula is
y~(V1+V2+V3)^2
For example
set.seed(15)
dd <- data.frame(V1=runif(50), V2=runif(50), V3=runif(50), y=runif(50))
lm(y~(V1+V2+V3)^2, dd)
Call:
lm(formula = y ~ (V1 + V2 + V3)^2, data = dd)
Coefficients:
(Intercept) V1 V2 V3 V1:V2 V1:V3 V2:V3
0.54169 -0.10030 -0.01226 -0.10150 0.38521 -0.03159 0.01200
Or, if you want to model all variables other than y,
lm(y~(.)^2, dd)
Call:
lm(formula = y ~ (.)^2, data = dd)
Coefficients:
(Intercept) V1 V2 V3 V1:V2 V1:V3 V2:V3
0.54169 -0.10030 -0.01226 -0.10150 0.38521 -0.03159 0.01200
Both are the same as
lm(y~V1+V2+V3+V1:V2+V1:V3+V2:V3, dd)
Call:
lm(formula = y ~ V1 + V2 + V3 + V1:V2 + V1:V3 + V2:V3, data = dd)
Coefficients:
(Intercept) V1 V2 V3 V1:V2 V1:V3 V2:V3
0.54169 -0.10030 -0.01226 -0.10150 0.38521 -0.03159 0.01200
You can use these formula with model.matrix to create a matrix
model.matrix(y~(V1+V2+V3)^2,dd)
